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  1. Jun 2025
    1. 数学自然主义

      好嘞~你问的是“数学自然主义”对吧?那就请系好安全带,我们准备冲出哲学的神庙,一头扎进“数就是干出来的!”的自然主义宇宙观。


      🎯 一句话简介:

      数学自然主义(Mathematical Naturalism) 是一种哲学立场,主张我们应该尊重数学实践本身, 不需要向哲学寻求“更高真理的认证”,只要数学在科学中有用、逻辑上自洽,就够了。

      简而言之:

      🗣️「你别问‘数学到底是不是真理’, 问它:有没有用?是不是科学家们正在用?是不是能继续发展?


      📚 背景:

      传统数学哲学老三派:

      | 哲学立场 | 简述 | | --------- | --------------------- | | 柏拉图主义 | 数学对象“真实存在”,我们在“发现”它们 | | 形式主义 | 数学是规则游戏,逻辑系统里的“棋盘对弈” | | 直觉主义 | 数学对象只有在我们能构造它们时才算“存在” |

      他们每天坐在哲学俱乐部里,讨论“真理有没有形而上学的颜色”。

      直到——

      🎩 一群自然主义者进场(比如 Penelope Maddy)说:

      “别吵了,数学家都没空理你们。人家在算黑洞、搞密码学、解 Navier-Stokes 方程呢。”

      于是:

      数学自然主义 = 向实践低头 + 拒绝形而上悬空。


      🧠 数学自然主义的核心观点:

      ✅ 1. 数学就是做出来的,不是想出来的

      不是靠沉思,而是靠证明、构造、计算、交流、发表、被同行采纳。

      ✅ 2. “有没有意义” ≈ “有没有用”

      能指导科学、构建模型、解决问题,就比“存在性证明”更重要。

      ✅ 3. 数学自我评估,不靠哲学托管

      哪套公理、哪种定义是否可接受,数学界自己内部商量,不需要“形而上仲裁”。

      ✅ 4. 没有“唯一数学真理”

      只有在不同目标下有用的体系,比如:

      • 实数 vs 超实数
      • 欧氏几何 vs 黎曼几何
      • ZFC集合论 vs Homotopy Type Theory

      都可用,都各有宇宙。


      🤔 举个现实栗子:

      科学家算黑洞时用到复数和微分几何; 加密工程师用的是数论和模运算; 这些工具不管有没有“存在性证明”,它们就是好用,能算准。

      Maddy 会说:

      “我们不需要相信复数‘客观存在’于宇宙, 只要它能让我们正确预测电子的行为,它就在物理里占了C位。”


      🎬 如果拍成短视频:

      📹 标题:《你还在问“数学是不是真的”?自然主义数学家只想说:哥在干活》

      🎭 场景: 哲学家问:“自然数真的存在吗?” 数学家转身:“它能让我建出量子计算模型,够用了。”


      🧠 金句集锦:

      “自然主义数学不在天上,也不在你脑中,它在我们正在运行的模型和公式里。”

      “数学不是关于‘真’,而是关于‘能不能跑起来’。”

      “科学走到哪里,数学就铺路到哪里。”


      🤹‍♀️ 延伸方向:

      • 📌 和集合论自然主义的关系(Maddy最爱的组合拳)
      • 📌 和建构主义的对话与冲突:建构主义强调“能构造”,自然主义说:“能应用就行”
      • 📌 和**多元宇宙数学观(Mathematical Multiverse)**联动:别纠结唯一数学世界,让它百花齐放!

      需要我为你设计一期《数学哲学大逃杀》?自然主义 vs 柏拉图主义 vs 建构主义火拼,最后观众投票决定谁能“证明世界”?📐🧠🔥

    1. Parcoursup 2025 : aborder sereinement la phase d’admission dès le 2 juin

      FCPE Nationale

      La phase d’admission principale de Parcoursup débutera à partir du lundi 2 juin 2025. Les candidats pourront consulter au fur et à mesure les réponses des formations et ils devront répondre aux propositions dans les délais indiqués par la plateforme.

      Voici le replay du webinaire organisé le 26 mai dernier avec Jérôme Teillard, chargé de mission Parcoursup au ministère chargé de l’Enseignement supérieur et de la Recherche, et une FAQ pour les futurs étudiants et leurs parents

      compte-rendu détaillé d'une réunion sur le processus d'admission post-bac, vraisemblablement via la plateforme Parcoursup.

      Les thèmes principaux abordés concernent le fonctionnement de la phase d'admission, les critères de sélection, les différents types de réponses possibles, la gestion des listes d'attente, l'importance de la réactivité des candidats, les dispositifs d'accompagnement et d'aide financière, ainsi que des conseils pratiques pour les lycéens et leurs parents.

      Thèmes Principaux et Faits Importants :

      1. Le Processus de Sélection et l'Algorithme Parcoursup :

      Il est clairement affirmé que Parcoursup n'examine pas les dossiers des lycéens et ne choisit pas leurs affectations. Ce sont les commissions d'examen des vœux (CEV) de chaque formation, qu'elles soient publiques ou privées, qui définissent les critères, évaluent les candidatures, et établissent des classements. "Ça n'est jamais l'algorithme de parcours. Chute qui examine les dossiers des lycéens. Ça n'est pas non plus parcouru qui choisit leur affectation. Ce sont bien au sein de chaque formation, qu'elle soit publique ou privée, une commission d'examen des vœux qui a défini des critères qui les a appliqués, qui a évalué les candidatures." (00:04:01.230 - 00:04:20.770) Ces commissions pondèrent des éléments de résultats scolaires et des éléments plus qualitatifs. Plus de 120 000 classements sont ensuite remontés à Parcoursup, qui intègre alors les priorités légales.

      2. Priorités Légales et Dispositifs d'Aide :

      Des priorités sont accordées à certains profils de candidats pour garantir l'équité et soutenir la mobilité ou l'intégration :

      Lycéens boursiers : "priorité pour des lycées boursiers. Puisque je rappelle que dechu pour chaque formation, y compris les formations les plus sélectives, il y a des taux minimum de lycées boursiers" (00:05:09.130 - 00:05:20.290). Une aide financière de 500 euros est proposée aux lycéens boursiers qui s'inscrivent dans une formation hors de leur académie de résidence pour accompagner la mobilité.

      Participation aux cordées de la réussite : Prise en compte par environ 40% des formations en 2025. Lycéens professionnels : Places priorisées pour accéder aux BTS.

      Lycéens technologiques : Places priorisées pour les Bachelors Universitaires de Technologie (BUT) car "ce sont les formations dans lesquelles ils réussissent le mieux." (00:06:08.830 - 00:06:11.780)

      Accès aux licences en tension : Priorité pour les candidats du secteur ou de l'académie, avec des exceptions géographiques (ex: Île-de-France). Lycéens français à l'étranger : Prioritaires dans toutes les universités en France métropolitaine ou outre-mer.

      3. La Phase d'Admission (à partir du 2 juin) :

      Types de réponses pour formations sélectives (BTS, BUT, CPGE, IFSI, etc.) :"Oui" : Proposition d'admission. Le candidat a un délai pour accepter ou renoncer.

      "Oui si" : Proposition d'admission sous condition de suivre un parcours d'accompagnement ou de remise à niveau (ex: modules disciplinaires). Ce n'est pas un "non", mais une "réponse avec alerte pour signaler qu'il y a un besoin de renfort". (00:21:48.610 - 00:21:57.520) L'an dernier, 26 000 étudiants ont été inscrits avec un "oui si".

      "Non" : Réponse négative. Le candidat peut consulter une notification pour demander des explications sur les critères et motifs de la décision. "Chaque lycée a un mois à compter de la publication... pour poser les questions" (00:40:29.190 - 00:40:34.390).

      Types de réponses pour les licences non sélectives :"Oui" : Admission.

      "Oui si" : Admission conditionnelle (voir ci-dessus).

      "En attente" : Le candidat est sur liste d'attente. L'évolution de cette liste dépend des réponses des candidats mieux classés.

      Réponses pour les vœux en apprentissage : La réponse est "candidature retenue sous réserve de contrats." (00:41:24.870 - 00:41:28.410) Le candidat doit trouver un contrat d'apprentissage pour que l'admission soit effective. Le calendrier est plus long, jusqu'en septembre. Il est conseillé d'accepter une proposition "étudiant" classique en attendant de trouver un contrat d'apprentissage.

      4. Gestion des Réponses et des Vœux en Attente :

      Fréquence des mises à jour : "Il n'y a qu'une mise à jour le matin. Donc ça ne sert à rien de se connecter 50 fois dans la journée." (00:23:28.800 - 00:23:31.600)

      Délais de réponse : Le délai de réponse initial est court (ex: jusqu'au 5 juin 23h59 pour les premiers jours). Ensuite, un rythme plus "pérenne" se met en place.

      Importance de répondre : "même quand on n'a pas envie d'une formation, il ne faut pas snoer par cour sup, il faut répondre. Vous avez le droit de dire oui ou de dire non, ce que je vous demande, c'est de répondre" (00:27:53.870 - 00:28:03.360).

      Hiérarchisation des vœux en attente : Depuis 2022, les candidats ayant des vœux en attente sont invités à les classer par ordre de préférence.

      Ce classement est personnel et confidentiel pour les formations.

      "La seule question à vous poser, c'est si j'avais une proposition d'admission sur ce vœu là, est ce que je l'accepterai et est ce que je renoncerai à la proposition que j'ai déjà acceptée?" (01:05:27.640 - 01:05:37.760)

      Conséquences du classement : L'acceptation d'un vœu plus haut dans la hiérarchie entraîne l'abandon des vœux inférieurs et la suppression des vœux en attente moins bien classés.

      "Si soit le v et pas le vœ deux, ça supprime le deux." (01:29:23.480 - 01:29:24.590) "l'objectif, ce n'est pas de faire piéger, mais c'est de vraiment que quelqu'un qui avait encore 15 jours en attente, s'il a la proposition qui satisfait i rend beaucoup ça évite que les listes d'attente, elles soient bloquées par certains qui attendent et qui voudraient les garder indéfiniment." (01:30:37.900 - 01:30:49.420)

      Possibilité de ne pas avoir de proposition : "Oui, on peut avoir des candidats... un tiers se trouve en attente sur ses vœux." (00:44:41.430 - 00:44:51.870) Cependant, en moyenne, les lycéens reçoivent près de six propositions sur les 33 jours du processus.

      La phase complémentaire : Une solution pour ceux qui n'ont pas de proposition ou qui souhaitent changer d'orientation. Elle permet de formuler de nouveaux vœux pour des formations ayant encore des places disponibles. Il est impossible de refaire un vœu pour une formation où l'on a déjà été refusé, car le jury s'est déjà prononcé.

      5. Outils et Accompagnement :

      Site d'entraînement Parcoursup : Des ressources (vidéos, règles d'or, quiz, situations fictives) sont disponibles pour aider les candidats à comprendre le fonctionnement et les règles de la phase d'admission. "il n'y a pas de boîte noire." (00:14:10.490 - 00:14:13.560)

      Numéro vert et réseaux sociaux : Assistance disponible. Mise à jour des coordonnées : S'assurer que les informations de contact (numéro de téléphone, adresse e-mail) sont correctes pour recevoir les notifications. "Le risque de ne pas avoir de proposition vient de la déconnexion avec son dossier." (00:46:00.670 - 00:46:03.950)

      6. Cas Particuliers :

      Refus du Bac au rattrapage : Si un candidat n'obtient pas son baccalauréat, la proposition d'admission est annulée.

      Informations sur le lycée d'origine : Les formations ont accès à l'établissement d'origine du candidat. Cependant, un critère géographique discriminant est interdit par la loi.

      Césure : Possibilité de demander une année de césure. Le candidat doit d'abord accepter une formation, puis l'établissement décidera d'accepter ou non le projet de césure, en fonction de sa "crédibilité" et de sa "cohérence". (01:35:54.560 - 01:35:59.700) La césure est différente d'une année sabbatique, car elle implique une inscription dans un établissement et potentiellement un statut social.

      En résumé, la réunion vise à démythifier le processus Parcoursup, en soulignant l'importance de l'évaluation humaine des dossiers par les formations et en détaillant les étapes claires et les règles de la phase d'admission. L'accent est mis sur la réactivité des candidats et la compréhension des différentes options et aides disponibles pour maximiser leurs chances d'intégrer la formation de leur choix.

    1. Résumé de la vidéo [00:00:01][^1^][1] - [00:23:45][^2^][2]:

      Cette vidéo présente un webinaire sur la commission d'appel et de recours dans l'enseignement primaire et secondaire en France. Elle explique le processus d'appel des décisions de passage ou de redoublement, les principes clés, et les droits des parents dans le système éducatif français.

      Points forts: + [00:00:13][^3^][3] Introduction au webinaire * Présentation du sujet et de l'importance des commissions d'appel et de recours * Discussion sur le rôle des conseils de classe et des conseils des maîtres + [00:01:00][^4^][4] La commission d'appel dans le primaire * Explication du fonctionnement et des raisons de faire appel * Détails sur les décisions de passage et les conditions de redoublement + [00:03:10][^5^][5] Le droit d'appel et le PPRE * Importance du droit d'appel comme principe de droit administratif * Mise en place obligatoire d'un Programme Personnalisé de Réussite Éducative (PPRE) en cas de redoublement + [00:07:01][^6^][6] Procédure d'appel et rôle des parents * Processus à suivre par les parents pour contester une décision * Conseils sur la préparation et la présentation de l'appel devant la commission + [00:10:46][^7^][7] Composition de la commission d'appel * Description des membres de la commission et de leur rôle impartial * Importance de la neutralité et de l'objectivité dans le processus d'appel + [00:14:01][^8^][8] Rôle des représentants des parents * Soutien et accompagnement des familles par les représentants des parents * Préparation des parents pour la présentation de leur cas devant la commission Résumé de la vidéo [00:23:46][^1^][1] - [00:46:07][^2^][2]:

      Cette partie du webinaire PEEP aborde la commission d'appel et de recours dans l'enseignement primaire et secondaire. Elle explique le rôle des membres du jury, les procédures de traitement des dossiers, et l'importance de prendre des décisions équitables et justifiées pour l'intérêt des élèves.

      Points forts: + [00:23:46][^3^][3] Fonctionnement de la commission * Détails sur la durée des sessions et l'importance de la préparation * Explication des rôles des membres et des accompagnateurs des familles + [00:27:45][^4^][4] Examen des dossiers * Importance de la complétude des dossiers pour les décisions * Procédure en cas de vice de forme et conséquences pour les familles + [00:31:26][^5^][5] Prise de décision * Critères pour juger les appels et l'importance de motivations objectives * Processus de vote et de notification des décisions aux familles + [00:37:03][^6^][6] Commissions d'appel dans le secondaire * Différences avec le primaire et importance des paliers d'orientation * Rôle des documents médicaux et sociaux dans les décisions d'appel Résumé de la vidéo [00:46:08][^1^][1] - [01:08:00][^2^][2]:

      Cette vidéo est un webinaire de la PEEP qui traite de la commission d'appel et de recours dans l'enseignement primaire et secondaire en France. Elle explique le processus d'appel des décisions du conseil de classe concernant l'orientation des élèves, en particulier lorsqu'il y a un désaccord sur le choix des spécialités ou des filières.

      Points forts: + [00:46:08][^3^][3] Le rôle du conseil de classe * Ne doit pas statuer sur les spécialités ou filières choisies par l'élève * Les erreurs du conseil de classe peuvent être corrigées en faveur de la famille + [00:50:40][^4^][4] Le processus d'appel * Les familles ont un délai pour faire appel des décisions * La commission d'appel examine les dossiers et entend les arguments des familles + [00:57:03][^5^][5] La composition de la commission d'appel * Comprend divers membres dont des représentants des parents d'élèves * Les absences de certains membres peuvent influencer la décision finale + [01:07:01][^6^][6] L'importance de l'orientation * Discuter des projets d'orientation avec les élèves et les familles * Les commissions d'appel doivent prendre en compte les erreurs du conseil de classe et les souhaits des familles Résumé de la vidéo [01:08:02][^1^][1] - [01:29:26][^2^][2] :

      Cette partie du webinaire aborde la commission d'appel et de recours dans l'éducation primaire et secondaire, en mettant l'accent sur le rôle des parents et les procédures à suivre.

      Points forts : + [01:08:02][^3^][3] Le rôle des parents dans la commission * Importance de l'expression et de la défense des intérêts de l'élève * Éviter de défendre l'indéfendable, se concentrer sur la réussite de l'élève + [01:10:09][^4^][4] Confidentialité et préparation * Obligation de confidentialité sur les délibérations et les votes * Préparation des parents pour leur intervention lors de la commission + [01:11:12][^5^][5] Cas particuliers des élèves de terminale * Droit de réinscription dans l'établissement d'origine après échec au baccalauréat * Possibilité de changement d'établissement pour une nouvelle dynamique + [01:14:11][^6^][6] Conseils pour les parents * Préparer un argumentaire solide et éviter les promesses irréalistes * Importance de la ponctualité et de la prise en compte de la fatigue lors des délibérations Résumé de la vidéo [01:29:27][^1^][1] - [01:30:54][^2^][2]:

      Cette partie du webinaire aborde la commission d'appel et de recours dans l'éducation primaire et secondaire. Elle explique le processus d'audition, le rôle du président en cas d'égalité des votes et la disponibilité des ressources du webinaire.

      Points forts: + [01:29:27][^3^][3] Processus d'audition * Capacité à écouter et lire simultanément * Importance de suivre l'audition tout en lisant les documents + [01:30:02][^4^][4] Rôle du président * En cas d'égalité des votes, la voix du président compte double * Règlement intérieur similaire à d'autres statuts + [01:30:21][^5^][5] Disponibilité des ressources * Les diaporamas sont disponibles sur le centre de ressources * Les webinaires sont accessibles sur la chaîne YouTube de la Fédération

    1. Note de synthèse : Les formes de la violence - Une analyse multifacette

      Ce document de synthèse explore la nature complexe de la violence, en s'appuyant sur les thèses de Didier Fassin et les exemples historiques et philosophiques cités dans les sources.

      Il met en lumière la dualité morale et politique de la violence, les diverses éthiques du refus de la violence, et la relecture contemporaine des rapports de force et de légitimité.

      1. La Violence : Jugement Moral et Réalité Politique Ambiguë

      La violence est intrinsèquement liée à un jugement moral de réprobation quasi-universel, qu'elle soit domestique, coloniale, ou étatique. Cependant, sa réalité politique est ambiguë :

      • Le Déni Concérté : La violence fait l'objet d'une condamnation générale, ce qui entraîne "le déni concerner la société toute entière ou des groupes particuliers".

      • Double Standard du Pouvoir : Le pouvoir prétend la prévenir et la combattre, mais "il s'en détournent en protègent les auteurs lorsqu'ils sont puissants mais les accablent quand ils appartiennent aux classes populaires aux minorités racisées aux populations étrangères".

      Cette contradiction entre le discours moral et la pratique politique est fondamentale.

      2. Les Éthiques du Refus de la Violence : Diversité et Complexité

      Le refus de la violence s'inscrit dans des traditions religieuses et philosophiques variées, mais sa signification est polysémique et complexe :

      • Traditions Religieuses : Le "Sermon sur la montagne" (Évangile de Matthieu) en est une expression canonique chrétienne :

      "Vous avez appris qu'il a été dit œil pour œil et dents pour dents et moi je vous dis de ne pas résister au méchant au contraire si quelqu'un te gifle sur la joue droite tends-lui l'autre joue."

      C'est l'éthos des premiers martyrs.

      • Traditions Philosophiques : Éric Weil (1967) vise "d'éliminer la violence", considérant cela comme "le secret de la philosophie".

      • Polysémie du Refus : Refuser la violence signifie-t-il la refuser de la commettre, d'y contribuer, de s'y soumettre, de la voir, de l'exhiber, d'en parler ? Ces questions ont des significations morales et politiques distinctes.

      • Légitimité de la Violence Contre l'Oppression : La question se pose de savoir si une réponse violente à l'oppression peut être légitime, et sous quelle forme, tant pour les mouvements de résistance que pour les situations individuelles de mauvais traitement.

      3. La Non-Violence : Manifestes et Figures Pionnières

      Plusieurs épisodes historiques illustrent le développement de la non-violence moderne :

      • "The Mask of Anarchy" de Percy Bysshe Shelley (1819) : Ce poème est considéré comme le premier manifeste moderne de la non-violence, écrit en réaction au massacre de Peterloo.

      Il exhorte la foule : "levez-vous comme des lions après le repos en nombre invincible secouez vos chaînes comme la rosée tombé sur vous pendant votre sommeil vous êtes nombreux ils sont peu".

      • Henry David Thoreau et la Désobéissance Civile : Son essai "Resistance to Civil Government" (1849) prône le refus de payer l'impôt fédéral pour protester contre l'esclavage et la guerre américano-mexicaine.

      Il condamne la violence structurelle de l'esclavage et la violence coloniale de la conquête.

      Thoreau suggère que "Sous un gouvernement qui emprisonne quiconque injustement la véritable place d'un homme juste est aussi en prison."

      Pour lui, le refus de l'impôt par un millier de citoyens ne serait "pas un acte violent et sanglant comme le serait de les payer et ainsi de permettre à l'État de commettre des violences et de répandre un sang innocent", définissant cela comme "une révolution pacifique".

      • Mahatma Gandhi et le Satyagraha : Inspiré par Thoreau, Gandhi a mobilisé des milliers d'Indiens et de Chinois en Afrique du Sud contre le "Black Act".

      Le Satyagraha, "attachement à la vérité" ou "force de la vérité", est une "arme d'effort qui exclut tout recours à la violence et cherche à accéder à la vérité".

      Pour Gandhi, "renverser l'oppresseur n'est qu'une demi-victoire le convaincre de se transformer est une victoire pleine et entière".

      La Marche du Sel (1930) en Inde en est un exemple emblématique.

      • Martin Luther King Jr. et le Mouvement des Droits Civiques : Fortement influencé par Thoreau, King a dirigé des campagnes non-violentes, notamment le boycott des bus de Montgomery et les manifestations de Birmingham.

      Il souligne l'importance de "réunir les preuves de l'existence de l'injustice", "négocier des améliorations", "développer un programme dit de purification basé sur l'apprentissage des pratiques de la nonviolence" et "passer à l'action pour provoquer une crise censé déboucher sur l'ouverture de discussion".

      King n'était pas contre l'État ni la Constitution, mais s'appuyait sur eux pour finir avec la ségrégation.

      4. La Violence Légitime de l'Opprimé : Une Perspective Contestée

      La question de la légitimité de la violence de l'opprimé est un point de divergence crucial :

      • Thoreau et John Brown : Bien qu'apôtre de la non-violence, Thoreau a défendu John Brown, un abolitionniste ayant utilisé des moyens violents.

      Thoreau adopte la position du "spectateur révolutionnaire non violent" qui "cherche à réduire la violence de la vie non seulement en refusant de commettre des actes violents mais également en formant une communauté de spectateurs non violents qui témoignent de l'usage de la violence pour en terminer avec l'oppression et l'extermination et l'exploitation".

      Il admet des circonstances où la violence serait "inévitable" si d'autres options sont inefficaces, en fonction de la gravité de la cause, de l'imminence du danger et de la proportionnalité.

      • Frederick Douglass : Cet ancien esclave a défendu le recours à la violence pour la liberté, arguant que "tous les êtres humains ont des droits fondamentaux à la vie et à la liberté la privation de la seconde la liberté et le risque de privation de la première la vie justifiant alors le recours à la violence".

      Pour lui, les propriétaires d'esclaves perdent leurs droits fondamentaux en privant autrui des siens.

      • Frantz Fanon et la Violence Décolonisatrice :

      Dans "Les Damnés de la Terre" (1961), Fanon défend la violence comme "indispensable au processus de décolonisation".

      Il décrit la rencontre entre colonisateur et colonisé "toujours déroulé sous le signe de la violence".

      Pour Fanon, la violence coloniale est non seulement physique mais aussi morale, "déshumanise et même à proprement parler l'animalise".

      La violence de la décolonisation est "doublement libératrice" : elle mène à l'indépendance et "débarrasse le colonisé de son complexe d'infériorité [...] elle le rend intrépide le réhabilite à ses propres yeux."

      Le texte de Fanon est moins un plaidoyer pour la violence qu'une "description lyrique et une et une explication subjective des faits qui conduisent à la décolonisation de la violence il révèle le caractère inéluctable nécessaire et finalement justifié".

      • Jean-Paul Sartre et la Radicalisation : La préface de Sartre aux "Damnés de la Terre" a radicalisé le propos de Fanon, par exemple avec la formule : "abattre un européen c'est faire d'une pierre de coup supprimer en même temps un oppresseur et un opprimé reste un homme mort et un homme libre".

      Cette interprétation, selon Alice Cherky, transforme l'analyse de Fanon de l'inéluctabilité de la violence en une "enthousiaste justification" du meurtre.

      • Jean Améry et le "Tabou de la Vengeance" : Survivant de la Shoah, Améry établit un parallèle entre la situation du colonisé et celle du détenu juif dans un camp, affirmant que "la liberté et la dignité doivent être acquises par la violence pour être liberté et dignité".

      Il défend le "tabou de la vengeance", arguant que "l'oppresseur ayant subi la violence que lui inflige l'opprimé devient son frère partageant son humanité".

      5. L'Inversion des Valeurs : La Violence du Colonisé comme Terrorisme

      Le texte souligne un "considérable déplacement moral et politique" et une "inversion des valeurs" au cours du dernier demi-siècle :

      • Légitimation Historique vs. Disqualification Actuelle : Kant, Thoreau, Douglass, Fanon, Sartre, Améry ont considéré la violence de l'opprimé comme légitime et une affirmation de l'humanité.

      Aujourd'hui, "la lutte du colonisé est désormais disqualifiée et sa résistance appelée terrorisme tandis que la politique du colonisateur est accepté et sa brutalité justifiée".

      • Redéfinition du Terrorisme : Historiquement, la "terreur" qualifiait un phénomène d'État (la Révolution française, régimes totalitaires).

      Progressivement, le terme "terrorisme" s'est différencié pour désigner "des pratiques et des groupes non étatiques et même s'opposant à l'État par des actions violentes".

      • Terrorisme : Arme du Faible ou Attribut de Délégitimation ? : Selon l'historien Henry Laurens, le terrorisme non étatique tue moins que la terreur d'État et sert à communiquer sur une situation d'oppression.

      Cependant, "en tant qu'attribut il sert aujourd'hui à délégitimer la lutte du faible et à éluder la violence du fort".

      Des figures comme Nelson Mandela, Menahem Begin, et Yasser Arafat ont été qualifiés de terroristes avant de devenir des chefs d'État et des Prix Nobel de la paix, illustrant la labilité de cette qualification.

      6. Refuser la Violence : Au-delà des Modèles Dualistes

      Le cours explore des formes plus subtiles de refus de la violence et remet en question les distinctions binaires :

      • Antigone et Bartleby : Ces figures littéraires représentent deux modalités de refus : la protestation explicite et spectaculaire (Antigone) et la résistance silencieuse et discrète (Bartleby).

      • Objecteurs de Conscience en Israël : Erica Weiss distingue la "résistance" publique (réfusnics) et l'"abstention" majoritaire mais invisible face au service militaire.

      L'abstention bénéficie d'une meilleure tolérance étatique, tandis que la résistance publique expose à des sanctions et à la stigmatisation.

      • Tactiques de Refus des Victimes : Pour les Palestiniens sous les bombes, refuser la violence n'est pas l'empêcher, mais "trouver le moyen de distraire ses enfants quand le vrombissement des avions et la détonation des explosions se font entendre", "s'attacher à des détails de la vie quotidienne en conservant la distance d'un humour tendre", ou "la nommer en décrire les effets sur les corps en exposer les conséquences sur les vies".

      • Violence Structurelle et Complexité des Rapports de Force : Honour Gun Gunai montre qu'en Turquie, c'est l'Autre (Arméniens, Grecs, Kurdes) qui est accusé de violence, jamais l'État. Alpana Roy (en Inde) et sa recherche sur les Naxalites soulignent l'importance de ne pas "se focaliser sur les opérations de guerri et d'oublier la violence structurelle".

      La division des opprimés par les oppresseurs ("diviser pour régner") est une stratégie courante.

      La Politique du Refus et la Violence Épistémique :

      • Audre Lorde : "les outils du maître ne démoliront jamais la maison du maître". Il faut refuser le cadre épistémologique du dominant.

      • Audra Simpson ("Mohawk Interruptus") : En refusant le passeport canadien, les Mohawks rejettent la manière dont l'État canadien les a traités et l'illégitimité de la législation coloniale. Elle plaide pour une "double souveraineté".

      • Gayatri Chakravorty Spivak ("Can the Subaltern Speak?") : La violence épistémique consiste à s'arroger le droit de dire qui est l'autre et de le réduire au silence.

      • Recherches Palestiniennes (Rana Barakat, Diana Allan, Mohamed El Kourd, Nasser Abouour) : Il s'agit de dépasser les analyses extérieures pour faire entendre les voix palestiniennes, refuser la déshumanisation et la censure, et affirmer leur existence au-delà de l'oppression ("writing Palestine studies").

      L'exemple de Nasser Abouour, qui fait du mur de sa cellule son compagnon et affirme ainsi sa liberté, est une illustration ultime de ce refus.

      Conclusion

      Le refus de la violence est un projet multiforme :

      • Il peut être non-violent, à la manière de Gandhi et King, acceptant de subir les coups pour dénoncer l'oppression.

      • Il peut être violent, comme prôné par Douglass et Fanon, en s'attaquant aux agents de l'oppression pour recouvrer liberté et dignité.

      • Il peut être une contestation de la conscription pour les dominants (objecteurs de conscience israéliens) ou une soustraction imaginative à la terreur pour les dominés (civils palestiniens).

      • Il implique de récuser la "division de l'espace moral qui conduit à fermer les yeux sur la brutalité des gouvernements et à blâmer les victimes qui se révoltent contre le contre leur répression".

      • Il s'agit également de rejeter les récits autorisés des vainqueurs qui effacent la version des vaincus, particulièrement dans le cas des peuples autochtones.

      • En somme, il y a "plusieurs demeures dans la maison de la nonviolence", et le cours invite à une "anthropologie du présent" qui explore les complexités de la violence et les responsabilités des sciences sociales face à la violence épistémique qui fait prévaloir la vision des dominants.

    1. 希腊哲学中的循环论

      你问到的“希腊哲学中的循环历史观”,可以说是古典哲学里的一块隐藏版时间炸弹: 不是线性的“昨天→今天→明天”,而是“起→盛→衰→灭→再起”的时间咕噜锅——永远在转,不许你逃!

      我们来一口一口吃掉这道时间浓汤:


      🔁 一句话速懂:

      希腊哲学里的“历史”,不是奔向某个终点,而是一个反复上演的宇宙剧本轮回: 政体、文明、人物、命运——该出现的总会再出现。你可以说它悲观,但它超稳定。


      🧠 核心理念:时间是个,不是一根线

      • 在基督教传统出现之前,古希腊哲学没有“救世历史”或“终末论”的概念;
      • 没有终极目标、也没有“进步主义”
      • 相反,他们认为:\n

      万事如春夏秋冬、昼夜轮替,有其“自然之律”,你只能顺天而行,而不能越轨去追“线性意义”。


      🧱 各大哲学家的循环观点速览:


      🔥 1. 赫拉克利特(Heraclitus)

      “万物流变”,但这个变化不是乱变,是**按照“逻各斯”(理性秩序)循环变的”。

      • 火是万物的本源,像宇宙的重启键;
      • 他认为:一切都会归于火焰,再由火焰生成新秩序,无限循环。

      就像宇宙的大肺在呼吸: 🔥➡️🌍➡️🔥➡️🌍➡️…


      💫 2. 毕达哥拉斯学派

      宇宙运行如音乐,节奏与比例构成宇宙的“永恒回旋”。

      • 灵魂会在生死之间轮回(灵魂转生);
      • 政体、灾难、英雄,也会在长久循环中再次归来

      你今天可能是个哲学家,来生是数学老师,下一世当柏拉图的猫都不稀奇 🐱。


      🏛️ 3. 柏拉图(Plato)

      他在《理想国》提出了一个核心概念:

      大年(Great Year):天体运行完一整轮所需的巨大周期 = 一次宇宙大洗牌。

      • 每到一个“宇宙年”结束,一切文明、灵魂、城邦重新开始;
      • “正义的政体”也无法逃过命运的衰败。

      就像上帝设定好了剧本,然后在每轮开场换个演员再演一遍。


      🏺 4. 亚里士多德(Aristotle)

      虽然更实用主义,但他也认为:

      政体演化是有周期规律的:\n 王政 → 贵族 → 民主 → 暴政 → 王政……

      政体不是单向进步,而是像政治蹦迪:你跳一圈回到原点,只是DJ换了首歌。


      🎭 经典循环逻辑:政治体制循环论(波利比乌斯)

      波利比乌斯是罗马时期的希腊历史学家,他总结了:

      所有政体都会像自然一样走过:

      1. 君主制(最开始很棒)
      2. 变成专制(权力腐败)
      3. 被贵族推翻(贵族统治)
      4. 贵族也腐败→民主(人民掌权)
      5. 民主变成暴民统治
      6. 最后出现救世主:回到君主制

      🔁 然后周而复始。

      是不是很像现在社交媒体上的评论区?先是讨论,然后骂战,最后呼唤“强人治国”😅


      🔮 哲学意义:

      希腊人看到:

      • 人性反复、自然规律反复、政体反复—— 所以他们构建了一种循环论历史观,本质上是:

      人的悲剧来自对“进步”的幻想,而智慧是接受宇宙的律动。


      🎬 总结一句话:

      在希腊哲学中,历史不是有意义地前进,而是有规律地原地转圈。 谁要是妄想终结历史,那才是笑话的主角。


      如果你想,我可以再来一期:

      • 《为什么历史总在重演?柏拉图告诉你这不是偶然》
      • 或者对比《基督教线性时间观 vs 希腊循环时间观》

      毕竟,不理解时间观,你就只是在时间里打工而已⏳📜

  2. www.planalto.gov.br www.planalto.gov.br
    1. preceito fundamental

      Entende-se por preceito fundamental, de forma ampla, as normas fundamentais e princípios explícitos e implícitos da Constituição Federal, tal como os princípios sensíveis previstos no art. 34.


      Informativo 1011 * ADPF 272 / DF * Órgão julgador: Tribunal Pleno * Relator(a): Min. CÁRMEN LÚCIA * Julgamento: 25/03/2021 (Presencial) * Ramo do Direito: Constitucional * Matéria: Controle de Constitucionalidade

      Ministério Público junto ao Tribunal de Contas Municipal e princípio da simetria

      Resumo - A arguição de descumprimento de preceito fundamental (ADPF) é instrumento eficaz de controle da inconstitucionalidade por omissão**.

      • O preceito veiculado pelo art. 75 da Constituição Federal (CF) aplica-se, no que couber, à organização, composição e fiscalização dos Tribunais de Contas dos Estados e do Distrito Federal e dos Tribunais e Conselhos de Contas dos Municípios, excetuando-se ao princípio da simetria os Tribunais de Contas do Município.

      • A arguição de descumprimento de preceito fundamental (ADPF) é instrumento eficaz de controle da inconstitucionalidade por omissão (1). Com efeito, a ADPF pode ter por objeto as omissões do poder público, quer totais ou parciais, normativas ou não normativas, nas mesmas circunstâncias em que ela é cabível contra os atos em geral do poder público, desde que essas omissões se afigurem lesivas a preceito fundamental, a ponto de obstar a efetividade de norma constitucional que o consagra.

      • O preceito veiculado pelo art. 75 da Constituição Federal (CF) (2) aplica-se, no que couber, à organização, composição e fiscalização dos Tribunais de Contas dos Estados e do Distrito Federal e dos Tribunais e Conselhos de Contas dos Municípios, excetuando-se ao princípio da simetria os Tribunais de Contas do Município (3).
      • De fato, a Constituição da República de 1988 manteve em funcionamento os Tribunais de Contas do Município existentes na data da sua promulgação (Tribunal de Contas do Município de São Paulo e do Rio de Janeiro), vedando a criação de novos Tribunais de Contas municipais, nos termos do § 4º do seu art. 31 (4). A existência especial de dois Tribunais de Contas municipais, absorvidos pela CF/1988, consagram o caráter sui generis e excepcional desses órgãos de controle remanescentes do modelo antes vigente.
      • Os Tribunais de Contas do Município — órgãos autônomos e independentes, com atuação circunscrita à esfera municipal, compostos por servidores municipais, com a função de auxiliar a Câmara Municipal no controle externo da fiscalização financeira e orçamentária do respectivo Município —, distinguem-se, portanto, dos Tribunais de Contas dos Municípios — órgãos estaduais, cuja área de abrangência coincide com o território do estado ao qual vinculados.
      • Inexiste paralelismo entre o modelo federal estabelecido ao Tribunal de Contas da União e o do Tribunal de Contas do Município, sendo essa mais uma das assimetrias constitucionais entre os entes federados, como, por exemplo, a ausência de Poder Judiciário, Ministério Público e Polícia Militar na esfera municipal. Ausente a instituição no plano municipal, não há o que se instituir, menos ainda sob o argumento de ausência de simetria do que se tem no estado e na União sobre o Ministério Público. Dessa forma, no caso, não é obrigatória a instituição e regulamentação do Ministério Público especial junto ao Tribunal de Contas do Município de São Paulo (5).
      • Com base nesse entendimento, o Plenário, por unanimidade, conheceu de ADPF e julgou improcedente o pedido nela formulado, por não vislumbrar omissão da Câmara de Vereadores e do Tribunal de Contas do Município de São Paulo na criação do Ministério Público especial junto ao Tribunal de Contas Municipal.

      ADI 4.180/DF STF - É lícito conhecer de ação direta de inconstitucionalidade como arguição de descumprimento de preceito fundamental, quando coexistentes todos os requisitos de admissibilidade desta, em caso de inadmissibilidade daquela.

    1. 《德国悲苦剧的起源》与寓言(Allegory)

      哇,你这是直奔本雅明最被低估、最费脑、最“黑暗哥特风”的作品之一:《德国悲剧的起源》(Ursprung des deutschen Trauerspiels)。如果说《机械复制时代的艺术作品》是他“最流行的哲学武器”,那《德国悲剧的起源》就是哲学深井中的炼金术笔记——迷人、晦涩、神秘、野心炸裂。

      接下来,让我带你走进这本全是黑色翅膀的思想迷宫


      📘一、这是什么书?到底在讲啥?

      别被标题骗了。这不是单纯讲德国戏剧史。

      它是本雅明1925年写的博士后资格论文(但没过,学术委员会都懵了)——表面分析17世纪德语世界的悲剧(Trauerspiel),实则提出一整套:

      关于历史、象征、语言、主权、死亡与时间的深层哲学批判。


      🎭二、什么是“哀悼剧” vs “真正的悲剧”?

      本书最核心的区分是:

      | 古典希腊的“悲剧” | 德国巴洛克的“哀悼剧”(Trauerspiel) | | ------------------- | -------------------------- | | 崇高、命运、英雄、神明介入 | 无神、混乱、政治、权谋、死亡堆积 | | 角色有清晰的悲剧命运 | 角色都像困兽,愚昧而庸俗 | | 最终带来“净化”(catharsis) | 最终只留下腐败与毁灭 |

      📌 本雅明认为:

      • 德国“哀悼剧”不是失败的悲剧,而是一种对现代政治绝望的真实呈现
      • 它不崇高、不洗涤灵魂、不升华死亡——它让你看见权力、死亡、语言之间的荒谬联动。

      🧠三、本书的几个哲学爆点

      1️⃣ 政治主权 = 死亡舞台

      “在哀悼剧中,主权不再神圣,而是通过尸体、斩首、法庭仪式维持自身。”

      他批判的是施密特式“主权决定例外”的暴力基础。王权只是通过制造死亡仪式来维护权力。

      也就是说:

      主权的真正戏剧性,不在“统治”,而在“合法地杀”。


      2️⃣ 象征 vs 标志(Symbol vs Allegory)

      这本书的最大理论贡献之一:

      | 象征(Symbol) | 一种凝聚统一的神秘整体,内外统一 | | ---------------- | ------------------------ | | 寓言(Allegory) | 破碎、多义、腐败的残骸,意味着失落与死亡 |

      📌 本雅明说: 现代性不是活在“象征的统一中”,而是在寓言的瓦砾中挣扎

      他钟情的不是“美学整合”,而是“破碎中发光的灰烬”。


      3️⃣ 历史不是线性,而是堆叠的废墟

      “历史是一片尸堆,而非一条金光大道。”

      本书预示了他后来在《历史哲学论纲》中发展出的历史观:

      • 拒绝进步史;
      • 强调“每一个时代都处于紧急状态”;
      • 强调“破碎时间中的觉醒”。

      🕯️四、这本书的风格与形式:注定冷门,却深刻得要命

      • 引用满天飞(西班牙哀悼剧、神秘主义、基督教象征学、文艺复兴图像学……)
      • 写作风格极度碎片化、非线性,仿佛是一本炼金师的思想实验室日志
      • 被许多人(包括本雅明生前自己)认为“没人看得懂”,但却孕育了无数后世思想(从德里达到阿甘本)

      📌一句话总结这本书:

      《德国悲剧的起源》是一部关于死亡、权力、语言和现代性破败的象征学诗学笔记本。 本雅明用“黑暗寓言”替代了启蒙史观,用“死亡装置”反转了古典崇高,用“腐败剧场”拆解了主权的神话。


      🧨要不要我帮你把它做成短片系列?

      比如:

      1. 《什么是哀悼剧?我们为什么不再相信悲剧?》
      2. 《主权者是舞台上的刽子手:巴洛克政治的剧场解构》
      3. 《象征已死,寓言是现代性的灵魂》
      4. 《死亡如何成为政治的一种美学》

      风格可以哥特、暗黑、镜面舞台感,视觉像一场穿越废墟与纸页的意识流话剧——要开场吗?🕯️📚🖤

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

      Learn more at Review Commons


      Reply to the reviewers

      Reply to the reviewers

      We would like to thank the reviewers for their comments, we see great value in the suggestions they made to strengthen our work. We are glad to see that they are in general positive about the manuscript. In the following, we include a point-by-point response to their comments, which are in general consistent with each other.


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

      In this manuscript, Sanchez-Cisneros and colleagues, examine how tracheal cell adhesion to the ECM underneath the epidermis helps shape the tracheal system. They show that if cell-ECM adhesion is perturbed the development of the tracheal system and the epidermis is disrupted. They also detect protrusions extending from the dorsal trunk cells towards the ECM. The work is novel, the figures are clear, and the questions are well addressed. However, I find that some of the claims are not completely supported by the data presented. I have some suggestions that will, I believe, clarify certain points.

      Major comments

      At the beginning of the results section as in the introduction the authors claim that "It is generally assumed that trunk displacement occurs due to tip cells pulling on the trunks so that they follow their path dorsally." This sentence is not referenced, and I do not know where it has been shown or proposed to be like this. In addition, the comparison with the ventral branches is also not referenced and the movie does not really show this. Forces generated by tracheal branch migration have been shown to drive intercalation (Caussinus E, Colombelli J, Affolter M. Tip-cell migration controls stalk-cell intercalation during Drosophila tracheal tube elongation. Curr Biol. 2008;18(22):1727-1734. doi:10.1016/j.cub.2008.10.062), but not dorsal trunk (DT) displacement.

      • *

      We agree that dorsal trunk displacement has not been discussed in previous works, just the fact that tip-cell migration influences stalk cell intercalation. We will rephrase this sentence, stating that dorsal trunk displacement has not been studied.

      However, to rule out the possibility that DT displacement and the phenotype observed in XXX is due to dorsal branch pulling forces, the authors should analyze what happens in the absence of dorsal branches (in condition of Dpp signalling inhibition as in punt mutants or Dad overexpression conditions).

      This is a great idea, and we thank the reviewer for suggesting this. We tried to achieve a similar goal by expressing a Dominant Negative FGFR (Breathless-DN) in the tracheal system, since its expression under btl-gal4 affects tip cell migration. However, the phenotype arises too late to have an effect in dorsal branch migration during the stages we were interested in analyzing. The alternative proposed by the reviewer should be more efficient, as blocking Dpp signalling prevents the formation of dorsal branches completely. We have just received flies carrying the UAS-Dad construct. We will express Dad under btl-gal4 and see how this affects dorsal trunk displacement.

      I am concerned about the TEM observations. The authors claim they can identify tracheal cells by their lumen (Fig. 2 C'). However, at stage 15, the tracheal lumen should be clearly identifiable, and the interluminal DT space should be wider relative to the size of the cells. In this case, there is nothing telling us that we are not looking at a dorsal branch or lateral trunk cell. Furthermore, at embryonic stage 15, the tracheal lumen is filled with a chitin filament, which is not visible in these micrographs. Also, there is quite a lot of tissue detachment and empty spaces between cells, which might be a sign of problems in sample fixing. Better images and more accurate identification of dorsal trunk cells is necessary to support the claim that "These experiments revealed a novel anatomical contact between the epidermis and tracheal trunks".

      The protocol that we use for TEM involves performing 1-μm sections that allow us to stage embryos and to identify the anatomical regions using light microscopy and then switch to ultra-thin sections for electron microscopy once we have found the right position within the sample. This approach also allows us to determine the integrity of the sample. We attach here a micrograph of the last section we analyzed before we decided to do the EM analysis. The asterisk (*) points to a region where the multicellular lumen of the trunk is visible. Due to its proximity to the posterior spiracles, we are confident this is the dorsal trunk and not the lateral trunk. We realize now, after comparing this image with an atlas of development (Campos-Ortega and Hartenstein, 2013), that the stage we chose to illustrate the interaction is a stage 14 embryo instead of the stage 15 we indicated in the manuscript. We will change the stage but given that dorsal closure has already started by stage 14, this does not affect our analysis. Still, we apologize for the mis-staging of the embryo.

      In the light-microscopy image, we have overlaid the EM section to the corresponding region of interest. We agree that the lumen should be thicker compared to the length of the cells, if the section would be cutting the trunk through its largest diameter. However, the protrusions we see do not emerge from the middle part of the trunk where the lumen is found but are seen towards the dorsal side of the trunk, where the lumen will no longer be visible in a longitudinal section as the ones we present. In the embryo shown in Figure 2A-C, our interpretation is that the section was done through a very shallow section of the lumen (represented below). We interpret this from the fact that we see abundant electron-dense areas which we think are adherens junctions from multiple cells. These junctions are visible in Figure 2C but are currently not labelled. We will add arrows to increase their visibility.

      Given that protruding cells lie at the base of dorsal branches, it would be expected that in some sections we would find the protrusions close to the dorsal branches. This is in fact what we show in the micrograph shown in Figure 2D, with a lower magnification overview image shown in Figure S2D. In this case, we see a cell in close proximity to the tendon cells on one side (Figure 2D), which is connected to a dorsal branch on the opposite side (shown in Figure S2D). This dorsal branch is clearly autocellular and chitin deposition is visible as expected for the developmental stage. Again, in Figure S2E we see an electron-dense patch near the lumen that corresponds to the adherens junctions that seal the lumen. We see that all this needs to be better explained in the manuscript, so we will elaborate on the descriptions, and incorporate the light microscopy micrograph to the supplemental figures. This should also aid with the anatomical descriptions requested by Reviewer #3. Nevertheless, we think these observations confirm that what we are describing are the contact points between the dorsal trunk and tendon cells.

      Timelapse imaging of the protrusions in DT cells is done with frames every 4 minutes (Video S3). This is not enough to properly show cellular protrusions and the images do not really show interaction with the epidermis. Video S4 has a better time resolution but it is very short and only shows the cut moment. Video S4, shows the cut, but the reported (and quantified recoil) is not clear. Nevertheless, the results are noteworthy and should be further analysed.

      We will acquire high temporal resolution time-lapse images using E-Cadherin::GFP and btl-gal4, UAS-PH::mCherry to show the behaviour of the protrusions on a short time scale.

      • *

      Provided these embryos survive, would it be possible to check if embryos after laser cutting will develop wavy DTs?

      We think it would be interesting to carry out this experiment, but the laser cut experiments were done under a collaborative visit and we would not be able to repeat it in a short-term period.

      What happens to the larvae under the genetic conditions presented in Fig.S3? Do they reach pupal stages? Do these animals reach adult stages?

      We have seen escapers out of these crosses, but we have not quantified the lethality of the experiment. We will analyse this and include it in the manuscript.

      The kayak phenotypes are very interesting and perhaps the authors could explore them more. As in inhibition of adhesion to the ECM, kay mutants display wavy dorsal trunks. Do they have defective adhesion? Fos being a transcription factor, this is a possibility. The authors should at least discuss the kay phenotypes more extensively and present a suitable hypothesis for the phenotype.

      We agree that the kayak experiments might bring more consequences than just preventing dorsal closure. We will complement this approach by blocking dorsal closure by other independent means. We will use pannier-gal4 (a lateral epidermis driver), engrailed-gal4 (a driver for epidermal posterior compartment), and 332-gal4 (an amnioserosa driver) to express dominant-negative Moesin. In our experience, this also delays dorsal closure and it should result in a similar tracheal phenotype as the one we see in kayak embryos.

      Minor comments

      Page 2 Line 9/10 The sentence "tracheal tubes branch and migrate over neighbouring tissues of different biochemical and mechanical properties to ventilate them." should be rewritten. Tracheal cells do not migrate over other tissues to ventilate them.

      We meant to say that tracheal cells migrate over other tissues at the same time as they branch and interconnect to allow gas exchange in their surroundings after tracheal morphogenesis is completed. Ventilation is used here as a synonym for gas exchange or breathing. We will rephrase this if the reviewer considers it confusing.

      Page 2 Line 24/25 The sentence "It has been generally assumed that trunks reach the dorsal side of the embryo because of the pulling forces of dorsal branch migration." needs to be backed up by a reference.

      As explained above, we will rephrase this sentence.

      Page 7 Line 32/23 In this sentence, the references are not related to dorsal closure "Similarly, the signals that regulate epidermal dorsal closure do not participate in tracheal development, or vice versa (Letizia et al., 2023; Reichman-Fried et al., 1994)."

      Our goal in this sentence was to explain that while JNK is required for proper epidermal dorsal closure, loss of JNK signaling in the trachea does not affect tracheal development (as shown by Letizia et al., 2023). At the same time, Reichman-Fried et al., 1994 described the phenotypes of loss of breathless (btl). We will remove this last reference as the work does not study the epidermis. We will rephrase the sentence as: “Similarly, the signals that regulate epidermal dorsal closure do not participate in tracheal development; namely, JNK signaling (Letizia et al., 2023).”

      Page 12 Line 1 "Muscles attach to epidermal tendon cells through a dense meshwork of ECM" this sentence must be referenced.

      We will add the corresponding references for this statement: (Fogerty et al., 1994; Prokop et al., 1998; Urbano et al., 2009). We will change “dense” for “specialized”.

      Fig. S1- Single channel images (A'-C' and A'-C') should be presented in grayscale.

      Fig. S4- Single channel images (A'-D' and A'-D') should be presented in grayscale.

      We will add the grayscale, single-channel images for these figures.

      Reviewer #1 (Significance (Required)):

      The findings shown in this manuscript shed light on the interactions and cooperation between two organs, the tracheal system and the epidermis. These interactions are mediated by cell-ECM contacts which are important for the correct morphogenesis of both systems. The strengths of the work lie on its novelty and live analysis of these interactions. However, its weaknesses are related to some claims not completely backed by the data, some technical issues regarding imaging and some over-interpreted conclusions.

      This basic research work will be of interest to a broad cell and developmental biology community as they provide a functional advance on the importance of cell-ECM interactions for the morphogenesis of a tubular organ. It is of specific interest to the specialized field of tubulogenesis and tracheal morphogenesis.

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

      Summary: In this paper, the authors explore the relationships between two Drosophila tissues - the epidermis and tracheal dorsal trunk (DT) - that get dorsally displaced during mid-late embryogenesis. The show a nice temporal correlation between the movements of the epithelia during dorsal closure and DT displacement. They also show a correlation between the movement of an endogenously tagged version of collagen and the DT, suggesting that the ECM may contribute to this coordinated movement. Through high magnification TEM, they show that tracheal cells make direct contact with the subset of epithelial cells, known as tendon cells, that also serve as muscle attachment sites. In between these contact sites, tracheae are separated from the epithelia by the muscles. Furthermore, the TEMs and confocal imaging of tracheal cells expressing a membrane marker at these contact sites show that the tracheal cells are extending filopodia toward the tendon cells. The authors then explore how a variety of perturbations to the ECM produced by the tendon and DT cells affect DT and epithelial movement. They find that expressing membrane-associated matrix metalloproteases (MMP1 or MMP2) in tendon cells as well as perturbations in integrin or integrin signaling components leads to delays in dorsal displacement as well as defective lengthening of the tracheal DT tubes. They find that defects in the association between the tracheal and epidermal ECM attachments affect dorsal displacement of the epidermis, disrupting dorsal closure.

      Major comments: I like the goals of this paper testing the idea that the ECM plays important roles in the coordination of tissue placement, and I think they have good evidence of that from this study. However, I disagree with the conclusions of the authors that disrupting contact between DT and the tendon cells has no effect on DT dorsal displacement. DT tracheal positioning is clearly delayed; the fact that it takes a lot longer indicates that the ECM does affect the process. It's just that there are likely backup systems in place - clearly not as good since the tracheal tubes end up being the wrong length.

      We agree with this view; in our deGradFP experiments we see a delayed DT displacement. We focused our analyses on the coordination with epidermal remodelling, which remained unaltered, but we in fact see a delayed progression in dorsal displacement of both tissues (Figure 5I-J). We will emphasize this in the corresponding section of the Results.

      It also seems important that the parts of the DT where the dorsal branches (DB) emanate are moving dorsally ahead of the intervening portions of the trachea. This suggests to me that the DB normally does contribute to DT dorsal displacement and that this activity may be what helps the DT eventually get into its final position. The authors should test whether the portions of the DT that contact the DB are under tension. If the DB migration is providing some dorsal pulling force on the DT, this may also contribute to the observed increases in DT length observed with the perturbations of the ECM between the tendon cells and the trachea - if tube lengthening is a consequence of the pulling forces that would be created by parts of the trachea moving dorsally ahead of the other parts. Here again, it would be good to test if the DT itself is under additional tension when the ECM is disrupted.

      • *

      We thank the reviewer for the suggested experiments. We agree with the fact that the dorsal branches should pull on the dorsal trunk and that this interaction should generate tension. Unfortunately, we are unable to test this with the experiments proposed by the reviewer, but we propose an alternative strategy to overcome this. We understand that the reviewer suggests we do laser cut experiments in dorsal branches to see if there is a recoil in the opposite direction of dorsal branch migration. We carried out our laser cut experiments using a 2-photon laser through a visit to the EMBL imaging facility, using funds from a collaborative grant. Funding a second visit would require us to apply for extra funding, which would delay the preparation of the experiments. We are aware of UV-laser setups within our university, however, UV-laser cuts would also affect the epidermis above the dorsal branches, which we think might contribute to recoil we would expect to see.

      Instead of doing laser cuts, we have designed an experiment based on the suggestion of reviewer #1 of blocking Dpp signaling (with UAS-Dad), which would prevent the formation of dorsal branches. We expect that in this experimental setup, the trunk will bend ventrally in response to thepulling forces of the ventral branches. We will also co-express UAS-Dad (to prevent dorsal branch formation) and UAS-Mmp2 (to ‘detach’ the dorsal trunk from the epidermis), and we would expect to at least partially rescue the wavy trunk phenotype.

      Minor comments: The authors need to do a much better job in the intro and in the discussion of citing the work of the people who made many of the original findings that are relevant to this study. Many citations are missing (especially in the introduction) or the authors cite their own review (which most people will not have read) for almost everything (especially in the discussion). This fails to give credit to decades of work by many other groups and makes it necessary for someone who would want to see the original work to first consult the review before they can find the appropriate reference. I know it saves space (and effort) but I think citing the original work is important.

      • *

      The reviewer is right; we apologize for falling into this practice. We will reference the original works wherever it is needed.

      Figure 7 is not a model. It is a cartoon depicting what they see with confocal and TEM images.

      We will change the figure; we will include our interpretations of the phenotypes we observed under different experimental manipulations.

      Reviewer #2 (Significance (Required)):

      Overall, this study is one of the first to focus on how the ECM affects coordination of tissue placement. The coordination of tracheal movement with that of the epidermis is very nicely documented here and the observation that the trachea make direct contact with the tendon cells/muscle attachment sites is quite convincing. It is less clear from the data how exactly the cells of the trachea and the ECM are affected by the different perturbations of the ECM. It seems like this could be better done with immunostaining of ECM proteins (collagen-GFP?), cell type markers, and super resolution confocal imaging with combinations of these markers. What happens right at the contact site between the tendon cell and the trachea with the perturbation? I think that at the level of analysis presented here, this study would be most appropriate for a specialized audience working in the ECM or fly embryo development field.

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

      Summary The manuscript by Sanchez-Cisneros et al provides a detailed description of the cellular interactions between cells of the Drosophila embryonic trachea and nearby tendon and epidermal cells. The researchers use a combination of genetic experiments, light sheet style live imaging and transmission electron microscopy. The live imaging is particularly clear and detailed, and reveals protruding cells. The results overall suggest that interactions mediated through the ECM contribute to development of trachea and dorsal closure of epidermis. One new aspect is the existence of dorsal trunk filipodia that are under tension and may impact tracheal morphogenesis through required integrin/ECM interactions.

      Major comments: - Are the key conclusions convincing? Generally, the key conclusions are well supported by the data, and the movies are very impressive. Interactions between the cell types are clearly shown, as is the correlations in their development. However, some of the images are challenging to decipher for a non-expert in Drosophila trachea, especially the EM images, and some of the data is indirect or a bit weak.

      We thank the reviewer for their observations. As mentioned above in response to Reviewer #1, we will add an overview image of the embryo we processed for TEM that is presented in Figure 2.

      The data related to failure of dorsal closure affecting trachea relies on one homozygous allele of one gene (kayak), and so this is somewhat weak evidence. Even though kay is not detected in trachea, there could be secondary effects of the mutation or another lesion on the mutant chromosome. The segments look a bit uneven in the mutant examples.

      • *

      The reviewer is right; as we proposed before, we will complement the kayak experiments with independent approaches that will delay dorsal closure.

      • Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether? Some of the experiments have low n values, especially in imaging experiments, so these may be more preliminary, but they are in concordance with other data.

      The problem we face in our live-imaging experiments is related to the probability of finding the experimental embryos. In most of our experiments we combine double-tissue labelling plus the expression of genetic tools. This generally corresponds to a very small proportion of the progeny. We will aim to have at least 4 embryos per condition.

      • Would additional experiments be essential to support the claims of the paper? Request additional experiments only where necessary for the paper as it is, and do not ask authors to open new lines of experimentation. Higher n-values would substantiate the claims. To strengthen the argument that dorsal closure affects trachea morphogenesis mechanically, the authors might consider using of a combination of kay mutant alleles or other mutant genes in this pathway to provide stronger evidence. Or they could try a rescue experiment in epidermis and trachea separately for the kay mutants.

      We think our experiments delaying dorsal closure using the Gal4/UAS system and a variety of drivers should address the point of the possible indirect effects of kay in tracheal development.

      • Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments. Imaging data can take awhile to obtain, but the genetic experiments could be done in a couple of months, and the authors should be able to obtain any needed lines within a few weeks.

      The reviewer is correct, we will be able to plan our crosses for the proposed experiments within a couple of months.

      • Are the data and the methods presented in such a way that they can be reproduced? Generally, yes. For the deGrad experiments, it is not clear how the fluorescent intensity was normalized - was this against a reference marker?

      Briefly, we used signals from within the embryo as internal controls. In the case of en-gal4, we normalized the signal to the sections of the embryo where en is not expressed and therefore, beta-integrin levels should not be affected. In the case of btl-gal4, we normalized against the signal surrounding the trunks which should also not be affected by the deGradFP system. We will elaborate on these analyses in the methods section.

      Are the experiments adequately replicated and statistical analysis adequate? There are several experiments with low n values, so this could fall below statistical significance. For example, data shown in Fig 1G: n=3; Fig 4D n=4, n=3; Fig 6J n=4

      As mentioned above, we will increase our sample sizes.

      Minor comments: - Specific experimental issues that are easily addressable. To make the TEM images more easily interpreted, it would be helpful to provide a fluorescent image of all the relevant cell types (especially trachea, epidermis, muscle, and tendon cells, plus segmental boundaries) labelled accordingly, so that reader can correlate them more easily with the TEM images. They might also include a schematic of an embryo to show where the TEM field of view is.

      We believe this should be addressed by adding the light microscopy section of the embryo with the TEM image overlaid as illustrated above.

      It is hard to be confident that the EM images reflect the cells they claim and that the filopodia are in fact that, at least for people not used to looking at these types of images.

      As we explained in the response to Reviewer #1, we will elaborate on the descriptions of our TEM data. We think that adding the reference micrograph will aid with the interpretations of the TEM images.

      • Are prior studies referenced appropriately? yes
      • Are the text and figures clear and accurate? yes

      • Do you have suggestions that would help the authors improve the presentation of their data and conclusions? The writing could be revised to be a bit clearer. Since the results of the experiments do not support the initial hypothesis, I found it a bit confusing as I read along. It may help to introduce an alterative hypothesis earlier to make the paper more logical and easy to follow. To be more specific, On page 3, the authors say they "show that dorsal trunk displacement is mechanically coupled to the remodelling of the epidermis" and also in the results comment that "With two opposing forces pulling the trunks other factors likely participate in their dorsal displacement, but so far these have remained unstudied." But that doesn't end up being what they find. The results from figure 5 and related interpretation on page 17 says "cell-ECM interactions are important for proper trunk morphology, but not for its displacement." So this was confusing to read and I would encourage the authors to frame the issues a bit differently in terms of tube morphogenesis.

      We see how this might be confusing. We will rewrite the introduction so that the work is easier to follow. To achieve this, we will state from the beginning the mechanisms we anticipate that regulate trunk displacement: 1) adhesion to the epidermis, 2) pulling forces from the dorsal branches and 3) a combination of both.

      Some minor presentation issues: What orientation is the cross-sectional view in figure 1C and movie 1?

      We will add a dotted box that indicates the region that we turned 90° to show the cross-section.

      On page 12, the authors say the "Electron micrographs also suggested high filopodial activity" but activity suggests dynamics that are not clear from EM. This could be re-phrased.

      As the reviewer indicates, we cannot conclude dynamics from a static image. We will replace “suggested high filopodial activity” with “revealed filopodial abundance”.

      Reviewer #3 (Significance (Required)):

      • Describe the nature and significance of the advance (e.g. conceptual, technical, clinical) for the field. The results of the paper are significant in that they characterize a mechanical interaction between two tissue types in development, which are linked by the extracellular matrix that sits between them. It is not clear to me that this describes a "novel mechanism for tissue coordination" as stated in the abstract, but it does characterize this type of interaction in a detailed cellular way.

      • Place the work in the context of the existing literature (provide references, where appropriate). For specialists, the work identifies a novel protruding cell type in the fly embryonic trachea, and provides beautiful and detailed imaging data on tracheal development. The "wavy" trachea phenotype is also uncommon and very interesting, so this result could be linked to the few papers that also describe this phenotype and be built up.

      • State what audience might be interested in and influenced by the reported findings. As it stands, this is most interesting for a specialized audience because it requires some understanding of the development of this system in particular. As it characterizes this to a new level of detail, it could be influential to those in the field. Some addition clarification of the results and re-framing could make the manuscript more clear and interesting for non-specialists.

      • Define your field of expertise with a few keywords to help the authors contextualize your point of view. Indicate if there are any parts of the paper that you do not have sufficient expertise to evaluate. I work with Drosophila and have studied embryonic and adult cell types, although not trachea specifically. I am familiar with all the genetic techniques and imaging techniques used here.

    2. 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 #1

      Evidence, reproducibility and clarity

      In this manuscript, Sanchez-Cisneros and colleagues, examine how tracheal cell adhesion to the ECM underneath the epidermis helps shape the tracheal system. They show that if cell-ECM adhesion is perturbed the development of the tracheal system and the epidermis is disrupted. They also detect protrusions extending from the dorsal trunk cells towards the ECM.

      The work is novel, the figures are clear, and the questions are well addressed. However, I find that some of the claims are not completely supported by the data presented. I have some suggestions that will, I believe, clarify certain points.

      Major comments

      At the beginning of the results section as in the introduction the authors claim that "It is generally assumed that trunk displacement occurs due to tip cells pulling on the trunks so that they follow their path dorsally." This sentence is not referenced, and I do not know where it has been shown or proposed to be like this. In addition, the comparison with the ventral branches is also not referenced and the movie does not really show this. Forces generated by tracheal branch migration have been shown to drive intercalation (Caussinus E, Colombelli J, Affolter M. Tip-cell migration controls stalk-cell intercalation during Drosophila tracheal tube elongation. Curr Biol. 2008;18(22):1727-1734. doi:10.1016/j.cub.2008.10.062), but not dorsal trunk (DT) displacement. However, to rule out the possibility that DT displacement and the phenotype observed in XXX is due to dorsal branch pulling forces, the authors should analyze what happens in the absence of dorsal branches (in condition of Dpp signalling inhibition as in punt mutants or Dad overexpression conditions).

      I am concerned about the TEM observations. The authors claim they can identify tracheal cells by their lumen (Fig. 2 C'). However, at stage 15, the tracheal lumen should be clearly identifiable, and the interluminal DT space should be wider relative to the size of the cells. In this case, there is nothing telling us that we are not looking at a dorsal branch or lateral trunk cell. Furthermore, at embryonic stage 15, the tracheal lumen is filled with a chitin filament, which is not visible in these micrographs. Also, there is quite a lot of tissue detachment and empty spaces between cells, which might be a sign of problems in sample fixing. Better images and more accurate identification of dorsal trunk cells is necessary to support the claim that "These experiments revealed a novel anatomical contact between the epidermis and tracheal trunks".

      Timelapse imaging of the protrusions in DT cells is done with frames every 4 minutes (Video S3). This is not enough to properly show cellular protrusions and the images do not really show interaction with the epidermis. Video S4 has a better time resolution but it is very short and only shows the cut moment. Video S4, shows the cut, but the reported (and quantified recoil) is not clear. Nevertheless, the results are noteworthy and should be further analysed. Provided these embryos survive, would it be possible to check if embryos after laser cutting will develop wavy DTs?

      What happens to the larvae under the genetic conditions presented in Fig.S3? Do they reach pupal stages? Do these animals reach adult stages?

      The kayak phenotypes are very interesting and perhaps the authors could explore them more. As in inhibition of adhesion to the ECM, kay mutants display wavy dorsal trunks. Do they have defective adhesion? Fos being a transcription factor, this is a possibility. The authors should at least discuss the kay phenotypes more extensively and present a suitable hypothesis for the phenotype.

      Minor comments

      Page 2 Line 9/10 The sentence "tracheal tubes branch and migrate over neighbouring tissues of different biochemical and mechanical properties to ventilate them." should be rewritten. Tracheal cells do not migrate over other tissues to ventilate them.

      Page 2 Line 24/25 The sentence "It has been generally assumed that trunks reach the dorsal side of the embryo because of the pulling forces of dorsal branch migration." needs to be backed up by a reference.

      Page 7 Line 32/23 In this sentence, the references are not related to dorsal closure "Similarly, the signals that regulate epidermal dorsal closure do not participate in tracheal development, or vice versa (Letizia et al., 2023; Reichman-Fried et al., 1994)."

      Page 12 Line 1 "Muscles attach to epidermal tendon cells through a dense meshwork of ECM" this sentence must be referenced.

      Fig. S1- Single channel images (A'-C' and A'-C') should be presented in grayscale.

      Fig. S4- Single channel images (A'-D' and A'-D') should be presented in grayscale.

      Significance

      The findings shown in this manuscript shed light on the interactions and cooperation between two organs, the tracheal system and the epidermis. These interactions are mediated by cell-ECM contacts which are important for the correct morphogenesis of both systems. The strengths of the work lie on its novelty and live analysis of these interactions. However, its weaknesses are related to some claims not completely backed by the data, some technical issues regarding imaging and some over-interpreted conclusions.

      This basic research work will be of interest to a broad cell and developmental biology community as they provide a functional advance on the importance of cell-ECM interactions for the morphogenesis of a tubular organ. It is of specific interest to the specialized field of tubulogenesis and tracheal morphogenesis.

    1. Here we find a recent increase in deforestation within ITs that coincided with a decrease in the protection and rights of indigenous people. We can now answer that: (1) there was a significant trend towards an increase in the area of forests deforested inside and outside the ITs between 2013 and 2021, with an important intensification in the 2019–2021 period, (2) within the ITs, deforestation increased significantly by 195% between 2019 and 2021, (3) in the 2019–2021 period, deforestation advanced 30% from the borders to the interior of the ITs and (4) about 96 million tons of CO2 were emitted due deforestation between 2013 and 2021 in the analyzed ITs.Based on our findings, we believe these territories will remain vulnerable without policy action to combat illegal deforestation in these territories and enforce the constitutional rights of indigenous peoples to protect their lands. For this, we present below a set of recommendations that can be adopted to achieve this objective by federal and state decision-makers:

      There seems to be less connection to the overall ecological impacts than I had hoped for. However, this article presents strong scientific data demonstrating the impact of deforestation on the Amazon.

    1. qualidade
      • ADI 6148
      • Órgão julgador: Tribunal Pleno
      • Relator(a): Min. CÁRMEN LÚCIA
      • Redator(a) do acórdão: Min. ANDRÉ MENDONÇA
      • Julgamento: 05/05/2022
      • Publicação: 15/09/2022

      ODS 3 - Saúde e Bem-Estar ODS 11 - Cidades e comunidades sustentáveis ODS 12 - Consumo e produção responsáveis ODS 15 - Vida terrestre

      AÇÃO DIRETA DE INCONSTITUCIONALIDADE. CONSTITUCIONAL, ADMINISTRATIVO E AMBIENTAL. PADRÕES DE QUALIDADE DO AR. CONSELHO NACIONAL DO MEIO AMBIENTE (CONAMA): COMPETÊNCIA PARA EXERCER JUÍZO TÉCNICO DISCRICIONÁRIO DE NORMATIZAÇÃO DA MATÉRIA. PRINCÍPIO DEMOCRÁTICO. AUTOCONTENÇÃO JUDICIAL. RESOLUÇÃO CONAMA Nº 491, DE 2018: NORMA CONSTITUCIONAL EM VIAS DE SE TORNAR INCONSTITUCIONAL. CONCESSÃO DO PRAZO DE 24 (VINTE E QUATRO) MESES PARA EDIÇÃO DE NOVA RESOLUÇÃO: OBSERVÂNCIA DA ATUAL REALIDADE FÁTICA.

      1. O Conselho Nacional do Meio Ambiente (CONAMA) é órgão colegiado criado pela Lei nº 6.938, de 1981, dotado de capacidade institucional e responsabilidade, para, a partir de estudos e debate colegiado, dispor sobre “normas e padrões compatíveis com o meio ambiente ecologicamente equilibrado e essencial à sadia qualidade de vida”.

      2. Diante das múltiplas vicissitudes e peculiaridades do caso, cabe, prioritariamente, ao CONAMA, como órgão regulador e no exercício da sua capacidade institucional, aquilatar, com devida atenção e aprofundado rigor técnico, qual o melhor conjunto de medidas apto a orientar a política de controle da qualidade do ar.

      3. Impropriedade do Poder Judiciário em adentrar, ou mesmo substituir, o juízo técnico discricionário realizado na elaboração e no aprimoramento da política pública em foco.

      4. Não se afigura salutar a conduta judicial de permanente e minudente escrutínio incidente sobre a condução das políticas públicas selecionadas pelo Administrador.

      5. Em se tratando de tema de complexa e controvertida natureza técnico-científica, cabe ao Poder Judiciário atuar com ainda maior deferência em relação às decisões de natureza técnica tomadas pelos órgãos públicos com maior capacidade institucional para o tratamento e solução da questão.

      6. Eventual atuação desta Suprema Corte no sentido de rever os critérios que redundaram na opção empreendida pelo CONAMA dependeria de manifesta falta de razoabilidade, de ausência de justificação ou de evidente abusividade na escolha empreendida pelo Administrador, não sendo este o caso dos autos.

      7. A Organização Mundial da Saúde (OMS) indica que as diretrizes por ela traçadas não devem ser aplicadas automática e indistintamente, devendo cada país levar em conta os riscos à saúde, sua viabilidade tecnológica, questões econômicas e fatores políticos e sociais peculiares, além do nível de desenvolvimento e da capacidade de cada ente competente para atuar na gestão da qualidade do ar.

      8. Sob a ótica do desenvolvimento sustentável, é necessário que sejam consideradas, pelo órgão regulador, o estágio mais atual da realidade nacional, das peculiaridades locais, bem como as possibilidades momentâneas de melhor aplicação dos primados da livre iniciativa, do desenvolvimento social, da redução da pobreza e da promoção da saúde pública, como elementos de indispensável consideração para construção e progressiva evolução da norma, de forma a otimizar a proteção ambiental, dentro da lógica da maior medida possível.

      9. Reconhecimento de que a Resolução CONAMA nº 491, de 2018, afigura-se “ainda constitucional”. Determinação ao CONAMA de edição de nova resolução sobre a matéria que considere (i) as atuais orientações da Organização Mundial de Saúde sobre os padrões adequados da qualidade do ar; (ii) a realidade nacional e as peculiaridades locais; e (iii) os primados da livre iniciativa, do desenvolvimento social, da redução da pobreza e da promoção da saúde pública.

      10. Se decorrido o prazo de 24 (vinte e quatro) meses, sem a edição de novo ato que represente avanço material na política pública relacionada à qualidade do ar, passarão a vigorar os parâmetros estabelecidos pela Organização Mundial de Saúde enquanto perdurar a omissão administrativa na edição da nova Resolução.

      11. Ação Direta de Inconstitucionalidade julgada improcedente.

    2. coletividade
      • ADPF 651
      • Órgão julgador: Tribunal Pleno
      • Relator(a): Min. CÁRMEN LÚCIA
      • Julgamento: 28/04/2022
      • Publicação: 29/08/2022

      ARGUIÇÃO DE DESCUMPRIMENTO DE PRECEITO FUNDAMENTAL. DIREITO CONSTITUCIONAL AMBIENTAL. MEDIDA CAUTELAR. DECRETO PRESIDENCIAL N. 10.224, DE 5.2.2020. EXCLUSÃO DA SOCIEDADE CIVIL DO CONSELHO DELIBERATIVO DO FUNDO NACIONAL DO MEIO AMBIENTE. DECRETO PRESIDENCIAL N. 10.239, DE 11.2.2020. EXCLUSÃO DOS GOVERNADORES DO CONSELHO NACIONAL DA AMAZÔNIA. DECRETO PRESIDENCIAL N. 10.223, DE 5.2.2020. EXTINÇÃO DO COMITÊ ORIENTADOR DO FUNDO AMAZÔNIA. ALEGADA AFRONTA À PROTEÇÃO AO MEIO AMBIENTE E PROIBIÇÃO AO RETROCESSO AMBIENTAL. ARGUIÇÃO DE DESCUMPRIMENTO DE PRECEITO FUNDAMENTAL JULGADA PROCEDENTE.

      1. Proposta de conversão de julgamento de medida cautelar em julgamento definitivo de mérito: ausência de complexidade da questão de direito e instrução dos autos. Precedentes.

      2. Nas normas impugnadas, a pretexto de reorganizar a Administração Pública federal quanto à composição do Conselho Deliberativo do Fundo Nacional do Meio Ambiental, do Conselho Nacional da Amazônia e do Comitê Orientador do Fundo Amazônia, frustra-se a participação da sociedade civil e dos Governadores dos Estados integrantes da Amazônia Legal na formulação das decisões e no controle da sua execução em matéria ambiental.

      3. A exclusão da participação popular na composição dos órgãos ambientais frustra a opção constitucional pela presença da sociedade civil na formulação de políticas públicas ambientais. Contrariedade ao princípio da participação popular direta em matéria ambiental, à vedação do retrocesso e ao princípio da isonomia.

      4. A eliminação da paridade na composição dos órgãos ambientais confere ao Poder Executivo federal o controle das suas decisões, neutralizando-se o caráter crítico e diversificado da fiscalização, que deve permear a condução dos trabalhos e políticas públicas.

      5. A organização administrativa em matéria ambiental está protegida pelo princípio de proibição do retrocesso ambiental, o que restringe a atuação do administrador público, de forma a autorizar apenas o aperfeiçoamento das instituições e órgãos de proteção ao meio ambiente.

      6. Arguição de descumprimento de preceito fundamental julgada procedente para a) declarar inconstitucional a norma prevista no art. 5º do Decreto n. 10.224/2020, pela qual se extinguiu a participação da sociedade civil no Conselho Deliberativo do Fundo Nacional do Meio Ambiente, restabelecendo-se quanto ao ponto o disposto no Decreto n. 6.985/2009, pelo qual alterado o art. 4º do Decreto n. 3.524/2000; b) declarar a inconstitucionalidade do Decreto n. 10.239/2020, especificamente no ponto em que se excluiu a participação de Governadores no Conselho Nacional da Amazônia Legal; e c) declarar a inconstitucionalidade do art. 1º, CCII, do Decreto nº 10.223/2020, especificamente no ponto em que se extinguiu o Comitê Orientador do Fundo Amazônia.

    3. Poder Público
      • ADO 59
      • Órgão julgador: Tribunal Pleno
      • Relator(a): Min. ROSA WEBER
      • Julgamento: 03/11/2022
      • Publicação: 16/08/2023

      ODS 13 - Ação contra a mudança global do clima ODS 15 - Vida terrestre ODS 16 - Paz, Justiça e Instituições Eficazes ODS 17 - Parcerias e meios de implementação

      Ação direita de inconstitucionalidade por omissão. Omissão inconstitucional da União quanto à implementação das prestações normativas e materiais de proteção da área compreendida como Amazônia Legal. O inadimplemento dos deveres constitucionais de tutela do meio ambiente pela União Federal, materializado na ausência de políticas públicas adequadas para a proteção da Amazônia Legal e na desestruturação institucional das formuladas em períodos antecedentes, configura estado normativo desestruturante e desestruturado em matéria ambiental na região. Omissão normativa quanto às obrigações referentes à ativação do Fundo Amazônia, cuja causa principal consiste na extinção dos mecanismos normativos essenciais para a gestão do Fundo. A consequência da paralisação do Fundo Amazônia consiste na suspensão dos ativos financeiros doados, atualmente na ordem de mais de R$ 3.000.000.000,00 (três bilhões de reais), fato que impossibilita a contratação de projetos voltados às ações de prevenção, combate e controle do desmatamento na Amazônia Legal. Classificação do Fundo Amazônia como instrumento de política pública financeira necessária ao adimplemento dos deveres de proteção ao meio ambiente na região da Amazônia Legal. Vedação do retrocesso em tutela ambiental. Procedência parcial dos pedidos.

      1. A controvérsia constitucional objeto da deliberação do Supremo Tribunal Federal é um dos temas jurídicos e sociais mais relevantes da atualidade, tanto na perspectiva nacional quanto internacional. A questão subjacente à controvérsia assume caráter humanitário, cultural e econômico de abrangente impacto na tessitura social e na estrutura constitucional, notadamente no núcleo normativo do art. 225, caput, §§ 1º e 4º, da Constituição Federal.

      2. O comportamento omissivo de desrespeito à Constituição por parte dos Poderes Públicos, seja legislador, administrador ou jurisdicional, produz como resultado quadro de inexistência de tutela dos direitos fundamentais e do arcabouço normativo constitucional ou de insuficiência no adimplemento dos deveres fundamentais de proteção.

      3. O como concretizar os direitos fundamentais integra o espaço de conformação prática dos Poderes Públicos, em especial do Legislativo e do Executivo. Todavia, a liberdade decisória inerente à formulação da política normativa tem como vetor de atuação o dever de tutela dos direitos fundamentais. A proteção não é discricionária, mas sim as formas de sua implementação, desde que observado o postulado da proporcionalidade em sua dupla face proibitiva: do excesso da intervenção na esfera de proteção de direitos fundamentais e da insuficiência de sua tutela.

      4. Os pedidos como formulados no sentido da adoção de providências administrativas enquadram-se na categoria de prestações normativas e fáticas derivadas da estrutura e necessidades da órbita de proteção do direito fundamental alegado.

      5. A audiência pública produziu aportes informativos e argumentativos essenciais, com esclarecimentos de questões fáticas e jurídicas necessárias para a contextualização e elucidação do problema posto.

      6. O quadro normativo e fático da Amazônia Legal traduz a realidade de um autêntico estado de coisas inconstitucional na Amazônia Legal, a revelar um cenário de tutela insuficiente e deficiente dos biomas patrimônios nacionais por parte do Estado brasileiro.

      7. O retrato contemporâneo da Amazônia Legal não responde aos deveres de tutela assumidos pelo Estado constitucional brasileiro, expressamente desenhado no art. 225 da Constituição e na arquitetura legislativa, como prescreve a Lei n. 12.187/2009, que instituiu a Política Nacional sobre Mudança do Clima – PNMC. Tampouco responde à normativa internacional, devidamente ratificada e promulgada pelo Estado brasileiro, a demonstrar seu comprometimento político e jurídico com a centralidade e importância da tutela do meio ambiente, em particular a proteção contra o desmatamento e as mudanças climáticas, a saber a Convenção-Quadro sobre Mudanças Climáticas de 1992 (Decreto n. 2.652 de 01 de julho de 1998); o Protocolo de Kyoto, de 2005 (Decreto n. 5.445 de 12 de maio de 2015); e o Acordo de Paris, aprovado no final de 2015 e em vigor desde 2016 (Decreto n. 9.073, de 05 de junho de 2017).

      8. A importância e a centralidade do Fundo Amazônia, como principal política pública financeira em vigor de apoio às ações de prevenção, controle e combate ao desmatamento, conservação das florestas e desenvolvimento sustentável, restou comprovada. Nesse sentido, os resultados fáticos obtidos com a implementação do PPCDAm e os depoimentos das organizações não-governamentais, dos secretários de Estado do Meio Ambiente, dos entes federados da Amazônia Legal e dos órgãos de controle e fiscalização envolvidos. Todavia, a centralidade do Fundo Amazônia como política pública financeira não significa inércia estatal, inclusive dos entes subnacionais, em formular outros instrumentos financeiros necessários ao financiamento das ações e planos de concretização da tutela do meio ambiente. Não é compatível com o modelo de federalismo cooperativo, em matéria ambiental, e com a normativa climática, a exclusividade de atuação da União Federal. Aos Estados igualmente compete concretizar objetivos de tutela dos seus biomas por meio de apresentação de resultados suficientes de redução do desmatamento para lograr políticas financeiras alternativas.

      9. A alteração na governança do Fundo Amazônia, com a extinção dos seus comitês, Comitê Orientador – COFA e Comitê Técnico-científico – CTFA, por meio da edição dos Decretos n. 9759/2019, n. 10.144/2020 e n. 10.223/2020, acarretou a suspensão da avaliação e aprovação de novos projetos no âmbito do Fundo e, por conseguinte, da aplicação dos recursos disponíveis em caixa. Coube apenas, em termos de operação do Fundo, a continuidade de execução dos projetos aprovados anteriormente.

      10. Da leitura e interpretação do art. 225 da Constituição Federal, fundamento normativo do Estado de Direito e da governança ambiental, infere-se estrutura jurídica complexa decomposta em duas direções normativas. A primeira, voltada ao direito fundamental, e a segunda relacionada aos deveres de proteção de responsabilidade dos poderes constituídos, atores públicos e da sociedade civil.

      11. A omissão inconstitucional configurada reside no comportamento comissivo do administrador, que instaurou marco normativo desestruturante do antecedente, sem as salvaguardas jurídicas necessárias para a manutenção de um quadro mínimo de adimplemento dos deveres de proteção ao direito fundamental ao meio ambiente equilibrado, mais especificamente de proteção dos patrimônios nacionais, tal como categorizados pelo art. §4º do art. 225 da Constituição Federal, e de cumprimento das obrigações climáticas firmadas.

      12. Apresenta-se, como medida jurisdicional adequada para a solução do problema posto, a invalidação dos dispositivos normativos que alteraram o modelo de governança do Fundo Amazônia. Como consequência, cabe à União tomar as providências administrativas necessárias para a reativação do Fundo, no que lhe compete.

      13. A omissão inconstitucional do Poder Executivo no que diz respeito ao funcionamento da política pública do Fundo Amazônia traz consequências em distintas atividades e operações do seu funcionamento, como recebimento de novos recursos, análise de novos projetos a serem financiados com valores já recebidos, em resposta aos resultados obtidos pelo Estado brasileiro na redução do desmatamento em momentos anteriores.

      14. As providências administrativas relacionadas as atividades de operação do Fundo é de competência do BNDES, responsável e gestor do Fundo. Por esse motivo, os pedidos b), c), d) e) formulados na inicial carecem de respaldo jurídico, porquanto fora da competência da União Federal e da abordagem constitucional desta demanda. O pedido de declaração de inconstitucionalidade do art. 1º, CCII, do Decreto nº 10.223/2020, no ponto em que extinguiu o Comitê Orientador do Fundo Amazônia, foi resolvido no julgamento da ADPF 651, de relatoria da Ministra Cármen Lúcia, quando o Tribunal, ao deferir o aditamento à inicial, declarou sua inconstitucionalidade.

      15. Procedência dos pedidos “a” e “f” para (i) declarar a inconstitucionalidade do art. 12, II, do Decreto nº 10.144/2019 e do art. 1º do Decreto nº 9.759/2019, no que se refere aos colegiados instituídos pelo Decreto nº 6.527/2008; e (ii) determinar à União Federal que, no prazo de sessenta dias, tome as providências administrativas necessárias para a reativação do Fundo Amazônia, dentro e nos limites das suas competências, com o formato de governança estabelecido no Decreto n. 6.527/2008.

      16. Ação direta julgada parcialmente procedente.

    1. Reviewer #4 (Public review):

      Thank you for the opportunity to provide a peer-review of this manuscript, which I first reviewed in 2023 under the title of '241,000 to 335,000 Years Old Rock Engravings Made by Homo naledi in the Rising Star Cave system, South Africa'. My review is brief as the authors state they have made "relatively minimal changes", so most of the comments I made in 2023 still stand. Some of the language is a little more temperate but the main issues of this potentially landmark study remain and undermine scientific acceptance of the findings claim. The fact that this is an initial report does not excuse it from the normal conventions of building arguments supported by empirical data. Again, the absence of a rock art expert on the authorial team causes recurring weaknesses still to be evident (would one ask a rock art expert to analyse a new fossil hominin skull for example?). Specifically, there are two major issues that need to be resolved before there is necessary and sufficient cause to assign the term 'rock engravings' to the marks in the Dinaledi chamber. These are authorship and dating.

       Authorship: The assertion that the 'rock engravings' are anthropogenic remains unsupported by empirical evidence, with a number of possible natural factors that could just as likely have caused the marks. Not to use image enhancements - which is standard in most rock art research and has been for some time - is a critical omission. The concerns stated about AI and data standards are not developed and the authors are directed to the literature in this field, for example this 2025 overview - https://www.sciencedirect.com/science/article/pii/S1296207424002516. Again, having a rock art expert would show the AI concern to be valid but easily addressed using Data Standards. In the almost 2 years since the first pre-print was released, there has been ample time for high resolution photographs and scans of the purported 'rock engravings'; analysis of which by relevant experts could properly physically characterise the marks and thus establish more or less likely agents for their production. European-based researchers in particular has utilised this approach on material such as the Blombos ochre and marked bone from Europe and Africa. None of these methods is invasive or destructive.

      To then go on and link Homo naledi to these markings is premature, especially when this landscape has been home to multiple hominins. Most rock art sites do not contain the physical bodily remains of their makers so we assign authorship based on dating (such as for Neanderthal era art in Europe for example); the second critical issue in this report:

       Dating: There is no direct or closely associated chronometric dating of the 'rock engravings' or their immediate context, so the age range claimed is unsupported. Rock art dating is notoriously difficult - and why researchers closely scrutinise dates produced. In this case, however, the chronological context is physically so far removed from these rock markings, as to be misleading at best and need to be discounted until a proper programme of dating has commenced. The sources cited for rock art dating tend to be out of date and it would be standard practice to have a geochronologist assess the rock-marked areas and then establish dating protocols.

      Authorship and dating are cornerstone of archaeological/paleoanthropological work and need to established in the first instance. Until that has been done commensurate with current standards in global rock art research this potentially landmark finding cannot be taken as probable, only as possible. This is a pity as the last decade or so has revolutionised our understanding of the socially complex world multiple hominin species lived in, and marked in utilitarian and symbolic ways. The conditions for acceptance of ancient rock art has thus never been better, but the Dinaledi example needs to revisit research first principles around authorship and dating to be included as a credible part of this larger context. It would have been good to see a commitment to a coherent research programme to this end for this case study.

      I hope these observations are useful. As above I keep them short as there has been minimal change to the 2023 ms, and my detailed comments on that remain with the first version of the work.

    2. Author response:

      The following is the authors’ response to the original reviews

      We thank the reviewers for their very constructive and helpful comments on the previous version of this manuscript. They have focused on some important issues and have raised many valuable questions that we expect to answer as research begins on these markings. As has been often the case with preprints, a number of experts beyond the four reviewers and editor have provided comments, questions, and suggestions, and we have taken these on board in our revision of the manuscript. In particular, Martinón-Torres et al. (2024) focused several comments upon this manuscript and raise some points that were not considered by the reviewers, and so we discuss those points here in addition to the reviewer comments.

      Some of us have been engaged in other aspects of the possible cultural activities of Homo naledi. After the discovery of these markings we considered it indefensible to publish further research on the activity of H. naledi within this part of the cave system without making readers aware that the H. naledi skeletal remains occur in a spatial context near markings on cave walls. Of course, the presence of markings leaves many questions open. A spatial context does not answer all questions about the temporal context. The situation of the Dinaledi Subsystem does entail some constraints that would not apply to markings within a more open cave or rock wall, and we discuss those in the text.

      We find ourselves in agreement with most of the reviewers on many points. As reflected by several of the reviewers, and most pointedly in the remarks by reviewer 1, the purpose of this preprint is a preliminary report on the observation of the markings in a very distinctive location. This initial report is an essential step to enable further research to move forward. That research requires careful planning due to the difficulty of working within the Dinaledi Subsystem where the markings are located. This pattern of initial publication followed by more detailed study is common with observations of rock art and other markings identified in South Africa and elsewhere. We appreciate that the reviewers have understood the role of this initial study in that process of research.

      Because of this, the revised manuscript represents relatively minimal changes, and all those at the advice of reviewers. Many thanks to all the reviewers for noting various typographic errors, missed references and other issues that we have done our best to fix in the revised manuscript.

      Expertise of authors. Reviewer 4 mentions that the expertise of the authors does not include previous publication history on the identification of rock art, and other reviewers briefly comment that experts in this area would enhance the description. AF does have several publications on ancient engravings and other markings; LRB has geological training and field experience with rock art. Notwithstanding this, we do take on board the advice to include a wider array of subject experts in this research, and this is already underway.

      Image enhancement. We appreciate the suggestions of some reviewers for possible strategies to use software filters to bring out details that may not be obvious even with our cross-polarization lighting and filtering. These are great ideas to try. In this manuscript we thought that going very far into software editing or image enhancement might be perceived by some readers as excessive manipulation, particularly in an age of AI. In future work we will experiment with the suggested approaches. 

      Natural weathering. In the process of review and commentary by experts and the public there has been broad acceptance that many of the markings illustrated in this paper are artificial and not a product of natural weathering of the dolomite rock. We deeply appreciate this. At the same time, we accept the comments from reviewers that some markings may be difficult to differentiate from natural weathering, and that some natural features that were elaborated or altered may be among the markings we recognize. On pages 3 and 4 we present a description of the process of natural subaerial weathering of dolomite, which we have rooted in several references as well as our own observations of the natural weathering visible on dolomite cave walls in the Rising Star cave system. This includes other cave walls within the Dinaledi Subsystem. We discuss the “elephant skin” patterning of natural dolomite surface weathering, how that patterning emerges, and how that differs from the markings that are the subject of this manuscript.

      Animal claw marks. Martinón-Torres et al. 2024 accept that some of the markings illustrated on Panel A are artificial, but they offer the hypothesis that some of those markings may be consistent with claw marks from carnivores or other mammals. They provide a photo of claw marks within a limestone cave in Europe to illustrate this point. On pages 5 and 6 of the revised manuscript we discuss the hypothesis of claw marks. We discuss the presence of animals in southern Africa that may dig in caves or mark surfaces. However the key aspect of the Malmani dolomite caves is that the hardness of dolomitic limestone rock is much greater than many of the limestone caves in other regions such as Europe and Australia, where claw marks have been noted in rock walls. As we discuss, we have not been able to find evidence of claw marks within the dolomite host bedrock of caves in this region, although carnivores, porcupines, and other animals dig into the soft sediments within and around caves. The form of the markings themselves also counter-indicates the hypothesis that they are claw marks. 

      Recent manufacture. One comment that occurs within the reviews and from other readers of the preprint is that recent human visitors to the cave, either in historic or recent prehistoric times, may have made these marks. We discuss this hypothesis on page 6 of the revised manuscript. The simple answer is that no evidence suggests that any human groups were in the Dinaledi Subsystem between the presence of H. naledi and the entry of explorers within the last 25 years. The list of all explorers and scientific visitors to have entered this portion of the cave system is presented in a table. We can attest that these people did not make the marks. More generally, such marks have not been known to be made by cavers in other contexts within southern Africa.

      Panels B and C. We have limited the text related to these areas, other than indicating that we have observed them. The analysis of these areas and quantification of artificial lines does not match what we have done for the Panel A area and we leave these for future work. 

      Presence of modern humans. We have observed no evidence of modern humans or other hominin populations within the Dinaledi Subsystem, other than H. naledi. Several reviewers raise the question of whether the absence of evidence is evidence of absence of modern humans in this area. This is connected by two of the reviewers to the observation that the investigation of other caves in recent years has shown that markings or paintings were sometimes made by different groups over tens of thousands of years, in some cases including both Neanderthals and modern humans. We have decided it is best for us not to attempt to prove a negative. It is simple enough to say that there is no evidence for modern humans in this area, while there is abundant evidence of H. naledi there.

      Association with H. naledi. Reviewer 2 made an incisive point that the previous version contained some text that appeared contradictory: on the one hand we argued that modern humans were not present in the subsystem due to the absence of evidence of them, yet we accepted that H. naledi may have been present for a longer time than currently established by geochronological methods.

      We appreciate this comment because it helped us to think through the way to describe the context and spatial association of these markings and the skeletal remains, and how it may relate to their timeline. Other reviewers also raised similar questions, whether the context by itself demonstrates an association with H. naledi. We have revised the text, in particular on pages 5 and 7, to simply state that we accept as the most parsimonious alternative at present the hypothesis that the engravings were made by H. naledi, which is the only hominin known to be present in this space.

      Age of H. naledi in the system. At one place in the previous manuscript we indicated that we cannot establish that H. naledi was only active in the cave system within the constraints of the maximum and minimum ages for the Dinaledi Subsystem skeletal remains (viz., 335 ka – 241 ka), because some localities with skeletal material are undated. We have adjusted this paragraph on page 7 to be clear that we are discussing this only to acknowledge uncertainty about the full range of H. naledi use of the cave system.

      Geochronological methods. Several reviewers discuss the issue of geochronology as applied to these markings. This is an area of future investigation for us after the publication of this initial report. As some reviewers note, the prospects for successful placement of these engraved features and other markings with geochronological methods depends on factors that we cannot predict without very high-resolution investigation of the surfaces. We have included greater discussion of the challenges of geochronological placement of engravings on page 6, including more references to previous work on this topic. We also briefly note the ethical problems that may arise as we go further with potentially  invasive, destructive or contact studies of these engravings, which must be carefully considered by not just us, but the entire academy.

      Title. Some reviewers suggested that the title should be rephrased because this paper does not use chronological methods to derive date constraints for the markings. We have rephrased the title to reflect less certainty while hopefully retaining the clear hypothesis discussed in the paper.

    1. complexités de la définition et de la qualification de la violence, en s'appuyant sur des exemples variés allant des violences domestiques aux conflits internationaux. Il met en lumière le caractère socialement construit de la violence, les enjeux moraux, légaux et politiques de sa reconnaissance et de sa caractérisation, et les dynamiques de pouvoir qui sous-tendent ces processus.

      1. La Nature Problématique de la Définition de la Violence

      La violence n'a pas de définition simple ou de délimitation précise. Sa reconnaissance dépend d'une qualification sociale, morale et légale.

      • Qualification sociale et historique: Ce qui est considéré comme violent évolue. Par exemple, "pendant des siècles, frapper son enfant lorsqu'on estimait qu'il avait commis une faute c'était le corriger [...] et puis à la fin du 19e siècle la chose est devenue répréhensible et punissable".
      • Dimensions multiples: La qualification de violence implique des dimensions "morale" (jugement social) et "légale" (jugement pénal). Dans des contextes de belligérance ou de pouvoir, une "dimension politique" s'ajoute, notamment pour nommer des violences "policières" ou des auteurs "terroristes".
      • Deux ordres de qualification:Reconnaissance (premier ordre): Établir si un acte est violent. Les auteurs présumés et leurs avocats tentent souvent de "requalification des faits" en les minimisant, justifiant ou excusant.
      • Caractérisation (second ordre): Une fois la violence reconnue, lui adjoindre un adjectif (ex: "violences domestiques", "violences sexuelles") ou la qualifier au regard du droit international (ex: "crime de guerre", "crime contre l'humanité", "génocide").

      2. La Violence perçue de l'Intérieur vs. de l'Extérieur : Le cas des mutilations génitales féminines

      Certaines pratiques considérées comme violentes par un regard extérieur ne le sont pas par la majorité des membres de la société qui les pratique.

      • L'excision au Soudan: L'anthropologue Janice Boddy, dans son livre Civilizing Women (2007), a étudié l'excision au Nord Soudan. Elle constate que, bien que douloureuse, "l'excision était attendue avec impatience et c'était la perspective de ne pas en faire l'expérience qui était redoutée". Elle produisait une "féminisation génitale idéalisée en terme de propreté et de pureté" et s'inscrivait dans une "esthétique morale" de différenciation genrée.
      • Relativisation historique et culturelle: Boddy invite à une comparaison avec des pratiques occidentales:
      • Au XIXe siècle, l'excision était pratiquée en Europe et en Amérique du Nord par la profession médicale pour soigner divers désordres (insomnie, stérilité, troubles psychologiques, etc.).
      • Aujourd'hui, la chirurgie génitale féminine à visée esthétique ("rajeunissement génital") est en augmentation dans le monde occidental, motivée par "les images de playmet circulant sur internet" et présentée comme une forme d'émancipation, "comme si dans ces deux derniers cas on pouvait faire fi de la domination masculine qu'elle manifeste y compris parmi les femmes par un effet de violence symbolique".
      • Domination masculine et violence symbolique: L'auteur souligne que ces pratiques, qu'elles soient traditionnelles ou modernes, peuvent être vues comme des manifestations de la domination masculine, ajoutant une "violence symbolique" à la violence physique.

      3. Le Rejet de la Souffrance : Le Rituel de "Kagnalen" en Casamance (Sénégal)

      Même si la violence n'est pas "nommée" comme telle, la souffrance qu'elle occasionne est souvent perçue par les victimes.

      • Le Kagnalen: Ce rituel Diola impose aux femmes présumées incapables d'assurer leur fonction procréatrice (stérilité, avortements répétés, décès d'enfants) un exil forcé, un changement d'identité souvent dépréciatif ("chienne qui ne retient pas le sperme"), un accoutrement ridicule, et des "tâches spécialement épuisantes" et "pratiques particulièrement dégradantes".
      • Souffrance reconnue: Malgré l'intégration du rituel dans une "division du travail social" qui rend les femmes responsables de la reproduction biologique, les femmes ayant subi le Kagnalen évoquent un "souvenir douloureux avec une profonde émotion ne pouvant retenir leur larmes" en mentionnant "la cérémonie initiale et la flagélation les années de mortification et d'avilissement l'isolement affectif et le labeur exténuant la peur continuelle des réprimandes et des sanctions".
      • Évitement et résistance: Certaines jeunes femmes tentent d'éviter le rituel en s'installant en milieu urbain ou en préférant les soins médicaux, "cherchaient à rompre le cercle de la violence symbolique dans lequel leur société tendait à les enfermer".

      4. La Violence non dite et les dynamiques de pouvoir

      La non-qualification de la violence dans l'espace public ne signifie pas que les victimes ne la reconnaissent pas.

      Reconnaissance implicite: "une chose peut exister à la fois dans le monde et dans la conscience qu'en ont les agents même s'il ne la nomme pas comme telle". Les femmes victimes de violences sexuelles reconnaissaient la "contrainte sur corps" sans se référer à une définition légale. Stratégies face à la violence reconnue: Les victimes peuvent "s'efforcer de l'éviter" (départ en ville), "essayer de la combattre" (campagnes de protestation) ou "s'en accommoder" (force de la tradition, coût trop élevé de la rupture), selon le modèle "Exit, Voice, and Loyalty" d'Albert Hirschman.

      5. La Violence d'État et le déni de la qualification

      La qualification de la violence est un enjeu majeur dans le cas de la violence d'État, où l'institution tente de l'occulter.

      • Monopole de la violence légitime: L'État revendique le "monopole de la violence légitime" (Max Weber). La différence réside entre "l'usage fondé de la force et le recours inapproprié à la violence".
      • Modalités d'évitement de la qualification des violences policières:Pression sur la victime pour ne pas porter plainte: Menaces ("il avait des petits frères qui avaient déjà fait des bêtises et que si lui portait plainte ce serait eux qui auraient des ennuis").
      • Contre-plainte: Accusations d'"outrage et rébellion contre agent dépositaire de l'autorité publique", qui servent souvent "un moyen de couvrir leur brutalité en la présentant comme un usage nécessaire de la force".
      • Justification: Extension légale de l'usage des armes par les forces de l'ordre, comme la loi de 2017 en France, pouvant aller jusqu'à une "autorisation de tuer au nom de la garantie de sécurité". Cette loi a entraîné un "quintuplement des tirs mortels pour refus d'obtempérer".
      • Définition de la violence d'État: Non seulement des violences commises par une institution agissant par délégation de l'État, mais aussi le fait que "l'État contribue à leur occultation en récusant leur existence en couvrant les déviances en apportant son soutien aux mises en cause [...] et en épargnant à l'inverse les auteurs par les réquisitions des parquets et les pressions sur les juges".
      • Paradoxe de la qualification: "c'est parce qu'il y a flagrant déni par l'État de la violence perpétrée par ses représentants et sous son commandement qu'on peut parler donc de violence d'état".

      6. Le Conflit des Interprétations dans les Conflits Internationaux : Israël-Palestine

      Les conflits internationaux sont aussi des "conflits d'interprétation" des faits, où les mots ont un poids politique et moral considérable.

      • L'herméneutique des discours: En s'appuyant sur Paul Ricœur, l'auteur propose une "herméneutique des discours", c'est-à-dire une "interprétation des interprétations", pour déchiffrer le "sens caché derrière le sens apparent".
      • L'attaque du 7 octobre 2023 : Deux interprétations radicales:Interprétation dominante occidentale (Israël et ses alliés): "acte d'antisémitisme", "le plus grand massacre antisémite de notre siècle", comparé à un "pogrome" ou la Shoah.
      • Enjeux et implications:Place les actes au "sommet de l'échelle des crimes".
      • Justifie "l'intensité de la réponse punitive à Gaza" et le "droit inconditionnel à se défendre" d'Israël.
      • Fragilise les accusations de crimes de guerre contre Israël, s'agissant d'éliminer une "organisation terroriste".
      • "Écarte toute possibilité de référence à ce qui s'est passé avant sa survenue et oblitèrent ainsi l'histoire de la Palestine".
      • Interprétation alternative (Hamas, pays du Sud, certains observateurs): "acte de résistance" inscrit dans une "guerre asymétrique" et une "séquence historique longue" de dépossession des Palestiniens depuis la Nakba (1948) et l'occupation des territoires (1967).
      • Enjeux et implications:Rappelle qu'il s'agit d'une "guerre dans le laquelle un état puissant assujetti un peuple", non d'une minorité persécutée.
      • Souligne "la passivité de la communauté internationale" et sa "complicité" face aux violations du droit international par Israël, privant les Palestiniens d'alternatives à la violence.
      • Permet d'appréhender le sens de l'action des acteurs à la lumière des "luttes contre domination étrangères".
      • Reconnaît "le poids de l'histoire" face aux "pratiques d'effacement des violences subies par les Palestiniens".
      • La qualification de génocide à Gaza:Arguments en faveur: Basée sur la Convention pour la prévention et la répression du crime de génocide (1948), citant "l'intention de détruire ou tout ou en partie un groupe national ethnique racial ou religieux comme tel" et les "quatre premières modalités" (nombre de morts, blessés, conditions de vie, entrave aux naissances). La "Cour internationale de justice [...] a affirmé le caractère plausible de la demande de prévention de la commission d'un génocide".
      • Arguments contre: "une nation composée en partie à sa création de rescapé d'un génocide ne peut pas être elle-même coupable de génocide". Les morts seraient des "victimes collatérales". La contestation se joue "sur le terrain du droit [...] mais également dans le cadre des rapports de force internationaux".

      Conclusion Générale

      La reconnaissance et la qualification de la violence sont des processus sociaux, complexes et souvent conflictuels.

      • Décalage entre victimes et auteurs: Les victimes "identifient bien la violence qu'elles subissent", tandis que les auteurs "soit la minimisent soit la justifie soit la conteste".
      • Enjeux de pouvoir: La "bataille se joue dans l'espace public [...] autant que sur le terrain légal", et est toujours "soutendues par des enjeux politiques".
      • Implications politiques et morales: La manière dont la violence est nommée et interprétée a des "conséquences presque opposées" sur la résolution des conflits, pouvant soit "disqualifier l'adversaire" et "exclure toute autre issue que son élimination", soit "ouvrir la possibilité d'une reconnaissance de tort et leur réparation".
    1. 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

      We thank the reviewers for their careful and thoughtful read of our work.

      Reviewer 1 helpfully suggested that the audience might not know what fuzzy matching is. The manuscript contains the following explanation of fuzzy matching:

      "That subjects had almost no exact matches to SARS-CoV-2-specific IGH sequences did not exclude the possibility that they have sequences that are functionally similar to these reference sequences. The same possibility exists for TRBs. A standard method for finding similar sequences is using the Levenshtein (edit) distance. Sequences with a distance of less than or equal to a tolerance t are considered similar (for example, sequences that differ by no more than t=1 amino acid). This is known as “fuzzy matching” with tolerance t. (Note that exact matches are just fuzzy matches with tolerance 0.)"

      We now also add the word "approximate" in conjunction with earlier uses of the word "fuzzy."

      Reviewer 2 asked whether we "focused on potential contributions [to CDR3 length variations] based on germline gene usage, rather than directly observed contributions from the V and J segments within the CDR3 regions;" the answer is, the latter. Reviewer 2 also pointed out that it would be valuable to have HLA typing for a more comprehensive analysis. We wholeheartedly agree and have added a sentence to this effect in the discussion.

      Reviewer 3 had several specific comments. The first was regarding the overall implication of the study. There are several:

      • binding capacity is as predictive as, and more robust than, prior approaches. As we write: "We found that repertoires’ binding capacity to known SARS-CoV-2-specific CD4+ TRBs performs as well as the best hand-tuned approximate or “fuzzy” matching at predicting a protective level of NAbs, while also being more robust to repertoire sample size and not requiring hand-tuning."

      • the importance of looking for unexpected patterns, for example in non-productive joins as was done here, and for global small-scale perturbations that together result in unavoidable signals. As we write, "B- and T-cell adaptive responses to SARS-CoV-2 infection and vaccination are surprising, subtle, and diffuse," and "One open question is to what extent infection affects antibody and TCR repertoires as a whole vs. enriching specific clones within it. One can refer to these ends of the continuum of possible effects as “diffuse” vs. “precise.”"

      • caution against over-interpreting correlations with specific gene segments and. As we write: "With these caveats in mind, to our knowledge previous studies have identified 20 IGH V genes to be enriched in sequences produced during various immune responses to SARS-CoV-2.8–16 Given that human genomes encode 54 IGH V genes,17 collectively these studies implicate 37% of V genes in the response to this single viral exposure, indicating that the SARS-CoV-2 response is either quite broad within individuals, quite heterogeneous among individuals, or both."

      Each of these challenges prevailing approaches, understanding, and conclusions about patterns and signatures in repertoire sequence. We should hope this would be of some benefit.

      Reviewer 3 also asked what type of vaccines the participants received. We have now clarified that they all received an mRNA vaccine: 80% receiving Pfizer Comirnaty and the rest receiving Moderna Spikevax.

      We looked at anti-spike neutralizing antibodies because this is where the evidence for neutralization is strongest. It would have been great to have diagnostics for every protein as well as Fc function, but these were not available and therefore not possible to study.

      Reviewer 3 noted that we mention that it is impossible to know a priori what study size would be adequate to identify public sequences comprehensively in COVID-19 and asks if 251 individuals are enough. Assuming this is in reference to the size of our study, we would like to point out that this study does not claim to identify public sequences comprehensively. The rationale is more is better. The statistics tell the reader the extent to which to reject the null hypotheses put forth.

      Regarding comorbidities: we probably could perform an analysis on their impact in a future study. We thank the reviewer for this idea.

      Regarding timing: samples were collected from the vaccinee cohort 4 to 84 days (mean = 44.3 days, standard deviation = 15.3 days) after administration of the initial vaccine dose. Supplementary Figure S13 shows sampling times vs. NAb titers.

      We feel the length of the introduction is required to contextualize the implications and benefits of this study.

      We were unable to find the typos referred to but did run the manuscript through spelling and grammar checks again. We thank the Reviewer for the thoughtful attentiveness.

    1. ARTICLE 27 - HOURS OF WORK AND OVERTIME
      1. UP#17- Art 27: Hours of work and overtime, Sec 1-General Provisions-Part A: Scheduling
      2. UP#18- Art 27: Hours of work and overtime, Sec 1-General Provisions-Part J: Telecommuting Plans
      3. UP#19-Art 27- Sec 2. Overtime Compensation for Non-Exempt Employees, Part B: Overtime
      4. UP#20- Art 27- Sec 3. Exempt Employees, A to D
  3. www.planalto.gov.br www.planalto.gov.br
    1. SNUC

      🏛️ 1. Unidades de Conservação por Natureza Jurídica da Propriedade

      A) Domínio Público

      (Uniões, Estados, Municípios ou Distrito Federal detêm a titularidade plena do imóvel. Expropriação quando há área privada.)

      • ESEC – Estação Ecológica

      • REBIO – Reserva Biológica

      • PARNA – Parque Nacional

      • FLONA – Floresta Nacional

      • RESEX – Reserva Extrativista

      • RDS – Reserva de Desenvolvimento Sustentável

      • REFA – Reserva de Fauna

      B) Domínio Privado

      (Permanece em mãos privadas, com restrições de uso impostas pela legislação.)

      • RPPN – Reserva Particular do Patrimônio Natural

      C) Domínio Misto (Público e/ou Privado)

      (A presença de imóveis privados é possível desde que compatível com a finalidade da UC.)

      • APA – Área de Proteção Ambiental

      • ARIE – Área de Relevante Interesse Ecológico

      • MONA – Monumento Natural

      • RVS – Refúgio da Vida Silvestre


      🚶 2. Unidades de Conservação por Possibilidade de Visitação Pública

      A) Proibida, salvo autorização para fins científicos - ESEC – Estação Ecológica

      • REBIO – Reserva Biológica

      B) Permitida com controle e restrições técnicas - PARNA – Parque Nacional

      • MONA – Monumento Natural

      • RVS – Refúgio da Vida Silvestre

      • FLONA – Floresta Nacional

      • RESEX – Reserva Extrativista

      • RDS – Reserva de Desenvolvimento Sustentável

      • REFA – Reserva de Fauna

      • APA – Área de Proteção Ambiental

      • ARIE – Área de Relevante Interesse Ecológico

      • RPPN – Reserva Particular do Patrimônio Natural


      🔬 3. Unidades de Conservação por Possibilidade de Pesquisa Científica

      A) Permitida com autorização prévia e restrições

      Todas as categorias, exceto quando vedado expressamente, admitem pesquisa científica.

      Observação relevante:

      • Em ESEC, a pesquisa com manipulação ambiental deve respeitar o limite de até 1.500 ha ou 3% da área da unidade, o que for menor (art. 10, § 4º da Lei 9.985/2000).

      • Em REBIO, a pesquisa é permitida sem interferência significativa no ambiente (art. 10, § 3º).


      🔧 4. Unidades de Conservação por Tipo de Uso dos Recursos Naturais

      A) Uso Indireto

      (Proibição de exploração dos recursos naturais) - ESEC – Estação Ecológica

      • REBIO – Reserva Biológica

      • PARNA – Parque Nacional

      • MONA – Monumento Natural

      • RVS – Refúgio da Vida Silvestre

      • RPPN – Reserva Particular do Patrimônio Natural

      B) Uso Direto

      (Exploração sustentável, conforme plano de manejo)

      • APA – Área de Proteção Ambiental

      • ARIE – Área de Relevante Interesse Ecológico

      • FLONA – Floresta Nacional

      • RESEX – Reserva Extrativista

      • RDS – Reserva de Desenvolvimento Sustentável

      • REFA – Reserva de Fauna


      🏛️ 5. Unidades de Conservação por Necessidade de Conselho Gestor

      A) Obrigatoriedade expressa na lei - PARNA – Parque Nacional (consultivo)

      • APA – Área de Proteção Ambiental (consultivo)

      • FLONA – Floresta Nacional (consultivo)

      • RESEX – Reserva Extrativista (deliberativo)

      • RDS – Reserva de Desenvolvimento Sustentável (deliberativo)

      B) Facultativo ou não exigido expressamente - ESEC – Estação Ecológica

      • REBIO – Reserva Biológica

      • MONA – Monumento Natural

      • RVS – Refúgio da Vida Silvestre

      • ARIE – Área de Relevante Interesse Ecológico

      • REFA – Reserva de Fauna

      • RPPN – Reserva Particular do Patrimônio Natural


      🎯 6. Unidades de Conservação por Objetivo Principal

      A) Preservação absoluta da natureza (Proteção Integral) - REBIO – biodiversidade

      • ESEC – pesquisa científica restrita

      • PARNA – ecossistemas e uso público controlado

      • MONA – atributos naturais notáveis

      • RVS – espécies ameaçadas

      B) Conservação com uso racional (Uso Sustentável) - FLONA – manejo florestal sustentável

      • RESEX – extrativismo tradicional

      • RDS – desenvolvimento comunitário sustentável

      • REFA – manejo de fauna

      • APA – ocupação humana compatível

      • ARIE – áreas frágeis e sensíveis

      • RPPN – iniciativa privada de preservação

    2. categorias

      As categorias de unidade de uso sustentável são:

      1. 2 Áreas;

      2. 1 Floresta;

      3. 4 Reservas


      1. Área de Proteção Ambiental (APA);

      2. Área de Relevante Interesse Ecológico (ARIA);

      3. Floresta Nacional (FLONA);

      4. Reserva Extrativista (RESEX);

      5. Reserva de Fauna (REFA);

      6. Reserva de Desenvolvimento Sustentável (RDS);

      7. Reserva Particular do Patrimônio Natural (RPPN).

    3. categorias

      As categorias de unidade de proteção integral são:

      1. 1 Estação (ESEC);

      2. 1 Reserva (REBIO);

      3. 1 Parque (PARNA);

      4. 1 Monumento (MONA);

      5. 1 Refúgio (RVS).

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

      Learn more at Review Commons


      Referee #3

      Evidence, reproducibility and clarity

      Summary

      The methods applied in this study were thoughtfully designed. The study's goals and the experiments performed to test several of their hypotheses were meticulously planned, ensuring that the research approach was robust and aligned with the objectives. The experimental design effectively addressed the key questions and provided reliable insights into the role of cryptic PTMs in protein function and disease mechanisms.

      This study investigates cryptic post-translational modification (PTM) sites in the human proteome and their role in protein folding and expression, with significant implications for disease mechanisms. This work seeks to bridge the gap between the abundance of identified PTM sites and their regulatory roles in signaling pathways. A key focus of the study is on intermediate protein conformations-states that exist between fully folded and unfolded structures to determine whether these transient states contribute to disease by affecting protein synthesis, activity, stability, and degradation. To classify PTM sites as cryptic or non-cryptic, the authors used AlphaFold-predicted structures and relative solvent accessibility (RSA) scores, excluding those within quasi-rigid domain interfaces. This enabled them to create a database of mapped PTM sites, distinguishing based on their cryptic nature. Their analysis revealed that most PTMs occur at solvent-exposed residues, but unexpectedly, one-third of tyrosine phosphosites were cryptic. To assess the impact of cryptic phosphorylation on protein expression, they performed molecular dynamics (MD) simulations on SMAD and CHK1 phosphsites, showing that cryptic sites can become transiently exposed during protein folding. Their computational simulations further supported the finding that this exposure enhancing the chances of being modified and ultimately a potential mechanism for destabilization of its structure (due to that modification) to trigger degradation in physiological conditions. Experimentally, western blotting and protein half-life measurements confirmed that phosphomimetic substitutions affected protein expression, supporting their hypothesis that cryptic phosphorylation can influence protein stability and function. From an evolutionary and functional perspective, their phylogenetic analysis using entropy scores indicates that cryptic sites are more conserved. They also show that the cryptic PTM sites identified in this study were found to be substituted by phosphomimetic mutations in tumor-suppressor proteins, leading to dysregulation of their function and suppression of downstream signaling essential for tumor cell death. This study provides a framework for mapping cryptic PTM sites and understanding their role within intermediate protein folding states. By linking cryptic PTMs to their effects on protein stability, signaling pathways, and disease progression, the findings highlight a potential regulatory mechanism through which cryptic modifications contribute to cancer and other diseases.

      Minor revisions

      1. Result 1 - Residues with pLDDT scores below 65 were excluded from the analysis. The high-confidence measure applies to individual residues, regardless of whether the domains they belong to are also predicted with high confidence. Identifying the number of domains containing PTMs with overall high-confidence predictions could provide better insights into the orientation of modified residues within domain structures. To assess the relationship between residue-specific confidence and domain stability, we can analyze the correlation between high-confidence modified residues and the overall prediction accuracy of their domains. This could be quantified using the average error scores of domain residues. Additionally, using the average pLDDT score would indicate how many individual residues were predicted with high local structural confidence. In contrast, the average PAE (Predicted Aligned Error) score would provide insights into how well each residue's position is predicted relative to others within the domain, reflecting overall domain structural confidence.
      2. "Approximately 65% of proteins with cryptic phosphosites contained only one or two such residues, while less than 10% had five or more sites (Supp. Figure 3)." To better interpret this trend, it would be useful to analyze the total number of cryptic PTMs on proteins part of this study, including all modification types-not just phosphorylation. This would help determine whether the observed pattern is specific to phosphorylation or if it extends to other post-translational modifications as well.
      3. For the validation of cryptic sites, selecting domains under 200 amino acids was mentioned. However, was there also a minimum length threshold applied, similar to the filtering criteria used for false positives (less than 40 ignored)?
      4. To test their hypothesis that phosphorylation affects protein expression, they selected candidates for serine and threonine but excluded tyrosine. What were the reasons for not including tyrosine-related PTMs in their analysis?
      5. Do we know that the regulatory role of S300 on PYST1 is associated with the dual specificity of the phosphatase, and is this why it was selected as a negative regulator? While the regulatory roles of the other analyzed phosphosites on SMAD and CHK1 are discussed, there is limited mention of the specific role of S300 on PYST1 within the scope of the study.
      6. When comparing the entropic scores between cryptic and non-cryptic residues, the medians are 0.43 and 0.52, respectively. Although this difference is not very high, they do observe that cryptic residues have lower scores than non-cryptic ones. The distributions also show greater overlap (Figure 6). I'm wondering if any statistical testing would help assess how distinct these two groups really are.
      7. Why did the authors choose to rely on AlphaFold data instead of examining PDB structures? I didn't see any explanation or rationale provided for preferring AlphaFold predictions over experimentally determined structures from the PDB.

      Significance

      Novelty - The concept that cryptic site modifications can dysregulate signaling in cancer and other diseases is known, but systematically categorizing PTM sites into cryptic and non-cryptic to generate hypotheses for a wide range of identified PTMs remains an underdeveloped approach. This study establishes a framework for classifying PTMs based on their structural accessibility, integrating AlphaFold predictions, molecular dynamics simulations, solvent accessibility analysis, and phylogenetic conservation metrics. This approach not only enhances our understanding of PTM-mediated regulatory mechanisms but also provides a foundation for exploring how cryptic modifications contribute to protein function, stability, and disease progression.

      Strengths - This study benefits from its use of multiple validation methods and false-positive filtering, resulting in a high-confidence dataset of annotated PTM sites. The combination of computational predictions and experimental analyses strengthens the validity of their findings. This integrative approach enhances the reliability of the data and provides a comprehensive understanding of cryptic versus non-cryptic PTMs in protein regulation.

      Limitations

      1. The study relies primarily on predicted protein structures (e.g., AlphaFold), without exploring experimentally derived structures, which could provide more accurate and physiologically relevant insights.
      2. While the research demonstrates the impact of cryptic PTMs on protein function, it would be valuable to also investigate non-cryptic sites from their annotated data. By examining the effects of modifications on these non-cryptic sites, the study could further validate the importance of the cryptic versus non-cryptic classifications and help clarify the functional relevance of both types of sites.

      Audience - The broader implications of this work extend to biomedical research, drug discovery, and therapeutic development. Researchers in cell signaling and systems biology who aim to understand which modification sites are crucial for evaluating the outcomes of signaling pathways can benefit from the insights generated by this study. It provides a pathway for identifying novel drug targets and enhances our understanding of disease mechanisms, particularly in cancer and other diseases. Additionally, this work encourages and motivates computational biologists to develop more efficient methods for capturing protein folding dynamics, enabling more accurate hypotheses regarding the effects of specific PTM sites and how they influence protein function and disease progression.

      My expertise lies primarily in structural biology, with a strong background in developing and utilizing bioinformatics and computational tools. While I currently have less hands-on experience with experimental techniques, my comprehensive understanding of experimental methodologies, combined with an awareness of the expected outcomes, has enabled me to effectively evaluate and interpret experimental results.

    2. 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

      Summary:

      This preprint uses bioinformatic and experimental approaches to explore the prevalence and consequences of the phosphorylation of residues normally buried in the hydrophobic core of proteins. By cross-referencing validated human phosphosites (PhosphositePlus) with the predicted 3D structures of the human proteome (from the AlphaFold predicted protein structure database), they identified potential "cryptic" phosphosites not expected to be solvent-accessible. They further refined the list using a variety of tools and conclude that a significant percentage (roughly 25%) of known phosphosites in folded domains are cryptic. They go on to experimentally test the consequences of mutating several of these sites in known proteins either to non-phosphorylateable or phospho-mimetic residues, and found that the phosphomimetic mutants had lower half-lives and average expression levels than either the wt or non-phosphorylatable versions. Finally, they show that putative cryptic phosphorylation sites are more highly conserved that those that are surface-accessible, and that some of these cryptic sites are found in tumor suppressor genes and that phosphomimetic mutations at these sites can be found in tumor mutation databases.

      Major comments:

      Overall the experimental approach is relatively straightforward, and in general the authors' interpretation of the results seems reasonable. There were several areas where I believe additional analysis or discussion might clarify the interpretation, however.

      1. It would be helpful if the authors could discuss whether there is any correlation between cryptic sites and the extent of experimental validation in the Phosphosite database (e.g. those that were only identified in one or a few MS experiments). It is difficult to determine stoichiometry of phosphorylation experimentally, but can any inference be made on the extent of phosphorylation of cryptic sites vs. more conventional sites located in IDRs or on the surface of globular domains?
      2. The authors note that a larger percentage of tyrosine phosphorylation sites are cryptic compared with serine/threonine sites. I assume that tyrosine itself is more highly enriched in the hydrophobic cores of proteins relative to serine or threonine, due to its bulky hydrophobic side chain. Is the increased proportion of cryptic tyrosine phosphorylation sites more, less, or the same as the proportion of tyrosine in hydrophobic cores relative to serine and threonine?
      3. Fig. 5D and E: I had some trouble interpreting these figures. Indicating where the native state is in the plots would be helpful (stated in text as lower right, but a rectangle on the plot would make this more obvious). The text discusses three metastable intermediates, but what is the fourth one shown on the figures (well A, close to the native state)? This could be more explicitly explained.
      4. The fact that phosphomimetic mutations of cyptic sites in SMAD2 and CHK1 lead to lower expression levels and shorter half-lives is not surprising, given the expected disruption of the hydrophobic core by introduction of a charged residue. The results certainly show that if phosphorylated, these sites would decrease expression and half-life. With respect to half-life, however, if the authors are correct and cryptic sites are predominately phosphorylated co-translationally, one would expect that the half-life curves for the wt protein would not be a simple exponential, but would instead reflect two distinct populations: those that are phosphorylated during translation, and are almost immediately degraded, and those that escape phosphorylation and have the same half-life as the non-phosphorylatable mutant. Are the actual experimental results consistent with this two-population model? If not, this would be evidence that some of these cryptic sites can be exposed post-translation, either by thermal fluctuation or biological interactions.
      5. The authors make a point that cryptic phosphosites are more highly conserved than non-cryptic phosphosites, but it is not clear to me whether it is the side chain itself or its ability to be phosphorylated that is conserved. Supplemental Fig. 9, if I am interpreting it correctly, would suggest it is the residue itself and not its phosphorylation that is conserved. If so, wouldn't this suggest that phosphorylation of these cryptic sites is just an inevitable consequence of the conservation of serine, threonine, and tyrosine residues in hydrophobic core regions? If the authors have evidence that argues against this simple hypothesis, they should discuss it (e.g., cryptic phosphosites are more highly conserved in some cases than non-phosphorylated tyrosine, serine, and threonine residues that are not solvent accessible).
      6. Regarding the evolutionary conservation of cryptic sites, have the authors taken into consideration that tyrosine-specific kinases, phosphatases, and reader domains first appeared in the first metazoans, and are for the most part not seen in non-metazoan eukaryotes? I notice some of the proteomes used for the conservation analysis include plants and yeast, which lack most tyrosine phosphorylation.
      7. I find the argument that phosphorylation of exposed core residues is part of normal protein quality control/proteostasis to be convincing. Can the authors provide any experimental evidence to support this model (for example, greater phosphorylation of cryptic sites under stress conditions)? I don't think these experiments are necessary, but would seem to be a logical next step and could be done quite easily through collaboration.
      8. The authors note at the end of the discussion that targeting cryptic phosphosites might be a strategy to selectively degrade some proteins in cancer. Practically, how would this work? I can't think of how, but perhaps the authors can provide more specific suggestions.

      Minor comment:

      1. Introduction: "It involves the addition of a phosphate to an hydroxyl group found in the side chain of specific amino acids, typically serine, threonine or tyrosine residues." Of course serine, threonine, and tyrosine are the only standard amino acids with a simple hydroxyl group, so "typically" is not needed here.

      Significance

      In my view this is an important study, bringing rigor and a broad proteomic perspective to a phenomenon that (to my knowledge) had not been carefully examined previously. In terms of the big picture, I am of two minds. On the one hand, showing that phosphorylation of hydrophobic core residues exposed during translation or the early stages of folding can regulate steady state levels of some proteins provides an intriguing new mechanism to control the complement of proteins in the cell, and is potentially an area of regulation in normal physiology or in disease. On the other hand, if this is just part of the normal proteostatic mechanisms (hydrophobic core residues exposed for too long consign the protein to degradation, before it can lead to aggregation and other problems), that is a little less interesting to me. I think future work to tease out whether this mechanism is actually regulated and used by the cell to transmit information will be key. But the first step is showing that the phenomenon is real and widespread, and in my view this preprint accomplishes that goal very well.

      I come from a background of studying post-translational modifications in signaling, hence my hope that a regulatory role can be found. But even if cryptic phosphorylation turns out to be unregulated, the work provides important new insight into normal proteostasis, and therefore is a valuable contribution. I should note that I don't have extensive expertise in bioinformatic methods or the computational tools to study protein dynamics, but I assume other reviewers will critically evaluate these methods.

    1. Reviewer #2 (Public review):

      Summary:

      The investigation provides a computational as well as biochemical insights into the (un)binding mechanisms of a pair of psychoactive substances into cannabinoid receptors. A combination of molecular dynamics simulation and a set of state-of-the art statistical post-processing techniques were employed to exploit GPCR-ligand dynamics.

      Strengths:

      The strength of the manuscript lies in usage and comparison of TRAM as well as Markov state modelling (MSM) for investigating ligand binding kinetics and thermodynamics. Usually MSMs have been more commonly used for this purpose. But as the authors have pointed out, implicit in the usage of MSMs lie the assumption of detailed balance, which would not hold true for many cases especially those with skewed binding affinities. In this regard, the author's usage of TRAM which harnesses both biased and unbiased simulations for extracting the same, provides a more appropriate way-out.

      Weaknesses:

      (1) While the authors have used TRAM (by citing MSM to be inadequate in these cases), the thermodynamic comparisons of both techniques provide similar values. In this case, one would wonder what advantage TRAM would hold in this particular case.

      (2) The initiation of unbiased simulations from previously run biased metadynamics simulations would almost surely introduce hysteresis in the analysis. The authors need to address these issues.

      (3) The choice of ligands in the current work seems very forced and none of the results compare directly with any experimental data. An ideal case would have been to use the seminal D.E. Shaw research paper on GPCR/ligand binding as a benchmark and then show how TRAM, using much lesser biased simulation times, would fare against the experimental kinetics or even unbiased simulated kinetics of the previous report

      (4) The method section of the manuscript seems to suggest all the simulations were started from a docked structure. This casts doubt on the reliability of the kinetics derived from these simulations that were spawned from docked structure, instead of any crystallographic pose. Ideally, the authors should have been more careful in choosing the ligands in this work based on the availability of the crystallographic structures.

      (5) The last part of using a machine learning-based approach to analyse allosteric interaction seems to be very much forced, as there are numerous distance-based more traditional precedent analyses that do a fair job of identifying an allosteric job.

      (6) While getting busy with the methodological details of TRAM vs MSM, the manuscript fails to share with sufficient clairty what the distinctive features of two ligand binding mechanisms are.

      Comments on revisions:

      The authors have addressed most of the queries of the reviewer in an adequate manner. However, The current code availability section just provides the link to Python files to generate the plots. It is not very useful in its current form. The code availability section should provide a proper GitHub page that shows the usage of TRAM for the readers to execute. While Pyemma has been cited for TRAM, a python note book to reproduce the TRAM would be very instructive.

    2. Author response:

      The following is the authors’ response to the original reviews

      Public Reviews: 

      Reviewer #1 (Public Review): 

      This manuscript presents insights into biased signaling in GPCRs, namely cannabinoid receptors. Biased signaling is of broad interest in general, and cannabinoid signaling is particularly relevant for understanding the impact of new drugs that target this receptor. Mechanistic insight from work like this could enable new approaches to mitigate the public health impact of new psychoactive drugs. Towards that end, this manuscript seeks to understand how new psychoactive substances (NPS, e.g. MDMB-FUBINACA) elicit more signaling through βarrestin than classical cannabinoids (e.g. HU-210). The authors use an interesting combination of simulations and machine learning. 

      We thank the reviewer for the comments. We have provided point by point response to the reviewer’s comment below and incorporated the suggestions in our revised manuscript. Modified parts of manuscripts are highlighted in yellow.   

      Comments:

      (1) The caption for Figure 3 doesn't explain the color scheme, so it's not obvious what the start and end states of the ligand are. 

      We thank the reviewer to point this out. We have added the color scheme in the figure caption. 

      (2) For the metadynamics simulations were multiple Gaussian heights/widths tried to see what, if any, impact that has on the unbinding pathway? That would be useful to help ensure all the relevant pathways were explored.  

      We thank the reviewer for the suggestion. We agree with the reviewer that gaussian height/width may impact unbinding pathway. However, we like to point out that we used a well-tempered version of the metadynamics. In well-tempered metadynamics, the effective gaussian height decreases as bias deposition progresses. Therefore, we believe that the gaussian height/width should have minimal impact on the unbinding pathway. To address the reviewer's suggestion, we conducted additional well-tempered metadynamics simulations varying key parameters such as bias height, bias factor, and the deposition rate, all of which can influence the sampling space. Parameter values for bias height, bias factor and deposition rate that we originally used in the paper are 0.4 kcal/mol, 15 and 1/5 ps<sup>-1</sup>, respectively. We explored different values for these parameters and projected the sampled space on top of previously sampled region (Figure S4). We observed that new simulations sample similar unbinding pathway in the extracellular direction and discover similar space in the binding pocket as well. 

      Results and Discussion (Page 10)

      “We also performed unbinding simulations using well-tempered metadynamics parameters (bias height, bias deposition rate and bias factor) to confirm the existence of alternative pathways (Figure S4). However, the simulations show that ligands follow the similar pathway for all

      metadynamics runs.”

      (3) It would be nice to acknowledge previous applications of metadynamics+MSMs and (separately) TRAM, such as the Simulation of spontaneous G protein activation... (Sun et al. eLife 2018) and Estimation of binding rates and affinities... (Ge and Voelz JCP 2022). 

      We appreciate the reviewer's feedback. We have incorporated additional citations of studies demonstrating the use of TRAM as an estimator for both kinetics and thermodynamics (e.g. Ligand binding: Ge, Y. and Voelz, V.A., JCP, 2022[1]; Peptide-protein binding kinetics: Paul, F. et al., Nat. Commun., 2017[2], Ge, Y. et al., JCIM, 2021[3]). Additionally, we have included references to studies where biased simulations were initially used to explore the conformational space, and the results were then employed to seed unbiased simulations for building a Markov state model. (Metadynamics: Sun, X. et al., elife, 2018[4]; Umbrella Sampling: Abella, J. R. et al., PNAS, 2020[5]; Replica Exchange: Paul, F. et al., Nat. Commun., 2017[2]).

      (4) What is KL divergence analysis between macrostates? I know KL divergence compares probability distributions, but it is not clear what distributions are being compared. 

      We apologize for this confusion. The KL divergence analysis was performed on the probability distributions of the inverse distances between residue pairs from any two macrostates. Each macrostate was represented by 1000 frames that were selected proportional to the TRAM stationary density. All possible pair-wise inverse distances were calculated per frame for the purpose of these calculations. Although KL divergence is inherently asymmetric, we symmetrized the measurement by calculating the average. Per-residue K-L divergence, which is shown in the main figures as color and thickness gradient, was calculated by taking the sum of all pairs corresponding to the residue. We have included a detailed discussion of K-L divergence in Methods section.  We have also modified the result section to add a brief discussion of K-L divergence methodology.

      Results and Discussion (Page 15)

      “We further performed Kullback-Leibler divergence (K-L divergence) analysis between inverse distance of residue pairs of two macrostates to highlight the protein region that undergoes high conformational change with ligand movement.”

      Methods (Page 33)

      “Kullback–Leibler divergence (K-L divergence) analysis was performed to show the structural differences in protein conformations in different macrostates[4,114] . In this study, this technique was used to calculate the difference in the pairwise inverse distance distributions between macrostates. Each macrostate was represented by 1000 frames that were selected proportional to their TRAM weighted probabilities. Although K-L divergence is an asymmetric measurement, for this study, we used a symmetric version of the K-L divergence by taking the average between two macrostates. Per residue contribution of K-L divergence was calculated by taking the sum of all the pairwise distances corresponding to that residue. This analysis was performed by inhouse Python code.”  

      (5) I suggest being more careful with the language of universality. It can be "supported" but "showing" or "proving" its universal would require looking at all possible chemicals in the class. 

      We thank the reviewer for the suggestion. In response, we have revised the manuscript to ensure that the language reflects that our findings are based on observations from a limited set of ligands, namely one NPS and one classical cannabinoid. We have replaced references to ligand groups (such as NPS or classical cannabinoid) with the specific ligand names (such as MDMB-FUBINACA or HU-210) to avoid claims of universality and prevent any potential confusion.

      Results and Discussion (Page 19)

      “In this work, we trained the network with the NPS (MDMB-FUBINACA), and classical cannabinoid (HU-210) bound unbiased trajectories (Method Section). Here, we compared the allosteric interaction weights between the binding pocket and the NPxxY motif which involves in triad interaction formation. Results show that each binding pocket residue in MDMBFUBINACA bound ensemble shows higher allosteric weights with the NPxxY motif, indicating larger dynamic interactions between the NPxxY motif and binding pocket residues(Figure S9).  The probability of triad formation was estimated to observe the effect of the difference in allosteric control. TRAM weighted probability calculation showed that MDMB-FUBINACA bound CB1 has the higher probability of triad formation (Figure 8A). Comparison of the pairwise interaction of the triad residues shows that interaction between Y397<sup>7.53</sup>-T210<sup>3.46</sup> is relatively more stable in case of MDMB-FUBINACA bound CB1, while other two inter- actions have similar behavior for both systems (Figures S10A, S10B, and S10C). Therefore, higher interaction between Y397<sup>7.53</sup> and T210<sup>3.46</sup> in MDMB-FUBINACA bound receptor causes the triad interaction to be more probable. 

      Furthermore, we also compared TM6 movement for both ligand bound ensemble which is another activation metric involved in both G-protein and β-arrestin binding. Comparison of TM6 distance from the DRY motif of TM3 shows similar distribution for HU-210 and MDMBFUBINACA (Figure 8B). These observations support that NPS binding causes higher β-arrestin signaling by allosterically controlling triad interaction formation.” 

      Reviewer #2 (Public Review): 

      Summary: 

      The investigation provides computational as well as biochemical insights into the (un)binding mechanisms of a pair of psychoactive substances into cannabinoid receptors. A combination of molecular dynamics simulation and a set of state-of-the art statistical post-processing techniques were employed to exploit GPCR-ligand dynamics. 

      Strengths: 

      The strength of the manuscript lies in the usage and comparison of TRAM as well as Markov state modelling (MSM) for investigating ligand binding kinetics and thermodynamics. Usually, MSMs have been more commonly used for this purpose. But as the authors have pointed out, implicit in the usage of MSMs lies the assumption of detailed balance, which would not hold true for many cases especially those with skewed binding affinities. In this regard, the author's usage of TRAM which harnesses both biased and unbiased simulations for extracting the same, provides a more appropriate way out. 

      Weaknesses: 

      (1) While the authors have used TRAM (by citing MSM to be inadequate in these cases), the thermodynamic comparisons of both techniques provide similar values. In this case, one would wonder what advantage TRAM would hold in this particular case. 

      We thank the reviewer for the comment. While we agree that the thermodynamic comparisons between MSM and TRAM provide similar values in this instance, we would like to emphasize the underlying reasoning behind our choice of TRAM.

      MSM can struggle to accurately estimate thermodynamic and kinetic properties in cases where local state reversibility (detailed balance) is not easily achieved with unbiased sampling. This is especially relevant in ligand unbinding processes, which often involve overcoming high free energy barriers. TRAM, by incorporating biased simulation data (such as umbrella sampling) in addition to unbiased data, can better achieve local reversibility and provide more robust estimates when unbiased sampling is insufficient.

      The similarity in thermodynamic estimates between MSM and TRAM in our study can be attributed to the relatively long unbiased sampling period (> 100 µs) employed. With sufficient sampling, MSM can approach detailed balance, leading to results comparable to those from TRAM. However, as we demonstrated in our manuscript (Figure 4D), when the amount of unbiased sampling is reduced, the uncertainties in both the thermodynamics and kinetics estimates increase significantly for MSM compared to TRAM. Thus, while MSM and TRAM perform similarly under the conditions of extensive sampling, TRAM's advantage lies in its robustness when unbiased sampling is limited or difficult to achieve. 

      (2) The initiation of unbiased simulations from previously run biased metadynamics simulations would almost surely introduce hysteresis in the analysis. The authors need to address these issues. 

      We thank the reviewer for the comment. We acknowledge that biased simulations could potentially introduce hysteresis or result in the identification of unphysical pathways. However, we believe this issue is mitigated using well-tempered metadynamics, which gradually deposit a decaying bias. This approach enables the simulation to explore orthogonal directions of collective variable (CV) space, reducing the likelihood of hysteresis effects(Invernizzi, M. and Parrinello, M., JCTC, 2019[6]).

      Furthermore, there is precedent for using metadynamics-derived pathways to initiate unbiased simulations for constructing Markov State Models (MSMs). This methodology has been successfully applied in studying G-protein activation (Sun, X. et al., elife, 2018[4]).

      Additional support to our observation can be found in two independent binding/unbinding studies of ligands from cannabinoid receptors, which have discovered similar pathway using different CVs (Saleh, et al., Angew. Chem., 2018[7]; Hua, T. et al., Cell, 2020[8]).   

      (3) The choice of ligands in the current work seems very forced and none of the results compare directly with any experimental data. An ideal case would have been to use the seminal D.E. Shaw research paper on GPCR/ligand binding as a benchmark and then show how TRAM, using much lesser biased simulation times, would fare against the experimental kinetics or even unbiased simulated kinetics of the previous report 

      We would like to address the reviewer's concerns regarding the choice of ligands, lack of direct experimental comparison, and the use of TRAM, and clarify our rationale point by point:

      Ligand Choice: The ligands selected for this study were chosen due to their relevance and well characterized binding properties. MDMB-FUBINACA is well-known NPS ligand with documented binding properties. This ligand is still the only NPS ligand with experimentally determined CB1 bound structure (Krishna Kumar, K. et al., Cell, 2019[9]). Similarly, the classical cannabinoid (HU-210) used in this study has established binding characteristics and is one of earliest known synthetic classical cannabinoid. Therefore, these ligands serve as representative compounds within their respective categories, making them suitable for our comparative analysis.

      Experimental Comparison: We have indeed compared our simulation results to experimental data, particularly focusing on binding free energies. In the result section, we have shown that the relative binding free energy estimated from our simulation aligns closely with the experimentally measured values. Additionally, Absolute binding energy estimates are also within ~3 kcal/mol of the experimentally predicted value.

      TRAM Performance: TRAM estimated free energies, and rates have been benchmarked against experimental predictions for various studies along with our study (Peptide-protein binding: Paul, F. et al., Nat. Commun., 2017[2]; Ligand unbinding: Wu, H. et al., PNAS, 2016[10]) . As the primary goal of this study is to compare ligand unbinding mechanism, we believe benchmarking against other datasets, such as the D.E. Shaw GPCR/ligand binding paper, is not essential for this work.

      (4) The method section of the manuscript seems to suggest all the simulations were started from a docked structure. This casts doubt on the reliability of the kinetics derived from these simulations that were spawned from docked structure, instead of any crystallographic pose. Ideally, the authors should have been more careful in choosing the ligands in this work based on the availability of the crystallographic structures. 

      We thank the reviewer for the comment. We would like to clarify that we indeed used an experimentally derived pose for one of the ligands (MDMB-FUBINACA) as the cryo-EM structure of MDMB-FUBINACA bound to the protein was available (PDB ID: 6N4B) (Krishna Kumar K. et al., Cell, 2019[9]). However, as the cryo-EM structure had missing loops, we modeled these regions using Rosetta. We apologize for this confusion and have modified our method section to make this point clearer. 

      Regarding HU-210, we acknowledge that a crystallographic or cryo-EM structure for this specific ligand was not available. We selected HU-210 because it is most commonly used example of classical cannabinoid in the literature with extensively studied thermodynamic properties. Importantly, our docking results for HU-210 align closely with previously experimentally determined poses for other classical cannabinoids (Figure S11) and replicate key polar interactions, such as those with S383<sup>7.39</sup>, which are characteristic of this class of compounds. 

      System Preparation (Page 22)

      “Modeling of this membrane proximal region was also performed Remodel protocol of Rosetta loop modeling. A distance constraint is added during this modeling step between C98N−term and C107N−term to create the disulfide bond between the residues. [74,76] 

      As the cryo-EM structure of MDMB-FUBINACA was known, ligand coordinate of MDMB- FUBINACA was added to the modeled PDB structure. The “Ligand Reader & Modeler” module of CHARMM-GUI was used for ligand (e.g., MDMB-Fubinaca) parameterization using CHARMM General Force Field (CGenFF).[77]”

      (5) The last part of using a machine learning-based approach to analyze allosteric interaction seems to be very much forced, as there are numerous distance-based more traditional precedent analyses that do a fair job of identifying an allosteric job. 

      We thank the reviewer for the valuable comment. Neural relational inference method, which leverages a VAE (Variational Autoencoder) architecture, attempts to reconstruct the conformation (X) at time t + τ based on the conformation at time t. In doing so, it captures the non-linear dynamic correlations between residues in the VAE latent space. We chose this method because it is not reliant on specific metrics such as distance or angle, making it potentially more robust in predicting allosteric effects between the binding pocket residues and the NPxxY motif.

      In response to the reviewer's suggestion, we have also performed a more traditional allosteric analysis by calculating the mutual information between the binding pocket residues and the NPxxY motif. Mutual information was computed based on the backbone dihedral angles, as this provides a metric that is independent of the relative distances between residues. Our results indicate that the mutual information between the binding pocket residues and the NPxxY motif is indeed higher for the NPS binding simulation (Figure S11).

      Method

      Mutual information calculation

      Mutual information was calculated on same trajectory data as NRI analysis. Python package MDEntropy was used for estimating mutual information between backbone dihedral angles of two residues. 

      Results and Discussion (Page 21)

      “To further validate our observations, we estimated allosteric weights between the binding pocket and the NPxxY motif by calculating mutual information between residue movements. Mutual information analysis reaffirms that allosteric weights between these residues are indeed higher for the MDMB-FUBINACA bound ensemble (Figure S11).”

      Mutual Information Estimation (Page 37)

      “Mutual information between dynamics of residue pairs was computed based on the backbone dihedral angles, as this provides a metric that is independent of the relative distances between residues. The calculations were done on same trajectory data as NRI analysis. Python package MDEntropy was used for estimating mutual information between backbone dihedral angles of two residues.[124]”

      (6) While getting busy with the methodological details of TRAM vs MSM, the manuscript fails to share with sufficient clarity what the distinctive features of two ligand binding mechanisms are. 

      We thank the reviewer for the insightful comment. In the manuscript, we discussed that the overall ligand (un)binding pathways are indeed similar for both ligands. Therefore, they interact with similar residues during the unbinding process. However, we have focused on two key differences in unbinding mechanism between the two ligands:

      (1) MDMB-FUBINACA exhibits two distinct unbinding mechanisms. In one, the linked portion of the ligand exits the receptor first. In the other mechanism, the ligand rotates within the pocket, allowing the tail portion to exit first. By contrast, for HU-210, we observe only a single unbinding mechanism, where the benzopyran ring leads the ligand out of the receptor. We have highlighted these differences in the Figure 6 and 7 and talked about the intermediate states appear along these different unbinding mechanisms. For further clarification of these differences, we have added arrows in the free energy landscapes to highlight these distinct pathways.

      (2) In the bound state, a significant difference is observed in the interaction profiles. HU-210, a classical cannabinoid, forms strong polar interactions with TM7, while MDMB-FUBINACA shows weaker polar interactions with this region.

      We have discussed these differences in the Results and Discussion section (Page 13-18) & conclusion section (Page 23-24).

      Recommendations for the authors:

      Reviewer #2 (Recommendations For The Authors): 

      (1) The authors should choose at least one case where the ligand's crystallographic pose is known and show how TRAM works in comparison to MSM or experimental report. 

      We thank the reviewer for the comment. We have used the experimentally determined cryo-EM pose for one of the ligands (i.e. MDMB-FUBINACA).  We have modified the manuscript to avoid confusion. (Please refer to the response of comment 4 of reviewer 2)

      (2) The authors should consider existing traditional methods that are used to detect allostery and compare their machine-learning-based approach to show its relevance. 

      We appreciate the reviewer’s comment. We have performed the traditional analysis by calculating mutual information between residue dynamics. We have shown that the traditional analysis matches with Machine learning based NRI calculation. (Please refer to the response of comment 5 of reviewer 2)

      (3) Figure 3 doesn't provide a guide on the pathway of ligand. Without a proper arrow, it is difficult to surmise what is the start and end of the pathway. The figures should be improved. 

      We appreciate the reviewer’s suggestion. In response, we have revised Figure 3 to clearly indicate the ligand’s unbinding pathway by adding directional arrows and labeling the bound pose. Additionally, we have updated the figure caption to better clarify the color scheme used in the illustration. 

      (4) The Figure 5 presentation of free energetics has a very similar shape for the two ligands. More clarity is required on how these two ligands are different. 

      We thank the reviewer for the comment. While the overall shapes of the free energy profiles for the two ligands are indeed similar, this is expected as both ligands dissociate from the same pocket and follow a comparable pathway. However, key differences in their unbinding mechanisms arise due to variations in the ligand motion within the pocket. Specifically, the intermediate metastable minima in the free energy landscapes reflect these differences. For instance, in the NPS unbinding free energy landscape, the intermediate metastable state I1 corresponds to a conformation where the NPS ligand maintains a polar interaction with TM7, while the tail of the ligand has shifted away from TM5. This intermediate state is absent in the classical cannabinoid unbinding pathway, where no equivalent conformation appears in the landscape.  

      (6) Page 30: TICA is wrongly expressed as 'Time-independent component analysis'. It is not a time-independent process. Rather it is 'Time structured independent component analysis'. 

      We thank the reviewer for pointing this out. TICA should be expressed as Time-lagged independent component analysis or Time-structure independent component analysis. We have used the first expression and modified the manuscript accordingly.  

      (7) The manuscript's MSM theory part is quite well-known which can be removed and appropriate papers can be cited. 

      We thank the reviewer for the comment. We have removed the theory discussion of MSM and cited relevant papers.

      “Markov State Model

      Markov state model (MSM) is used to estimate the thermodynamics and kinetics from the unbiased simulation.[56,91] MSM characterizes a dynamic process using the transition probability matrix and estimates its relevant thermodynamics and kinetic properties from the eigendecomposition of this matrix. This matrix is usually calculated using either maximum likelihood or Bayesian approach.[56,97] The prevalence of MSM as a post-processing technique for MD simulations was due to its reliance on only local equilibration of MD trajectories to predict the global equilibrium properties.[92,93] Hence, MSM can combine information from distinct short trajectories, which can only attain the local equilibrium.[94–96]  

      The following steps are taken for the practical implementation of the MSM from the MD data. [4,17,98–100]”

      (8) A proper VAMP score-based analysis should be provided to show confidence in MSM's clustering metric and other hyperparameters. 

      We thank the reviewer for the recommendation. VAMP-2 score based analysis had been discussed in the method section.  We estimated VAMP-2 score of MSM built with different cluster number and input TIC dimensions (Figure S15). Model with best VAMP-2 was selected for comparison with TRAM result.

    1. Reviewer #1 (Public review):

      Summary:

      This study addresses the roles of polyunsaturated fatty acids (PUFAs) in animal physiology and membrane function. A C. elegans strain carrying the fat-2(wa17) mutation possess a very limited ability to synthesize PUFAs and there is no dietary input because the E. coli diet consumed by lab grown C. elegans does not contain any PUFAs. The fat-2 mutant strain was characterized to confirm that the worms grow slowly, have rigid membranes, and have a constitutive mitochondrial stress response. The authors showed that chemical treatments or mutations known to increase membrane fluidity did not rescue growth defects. A thorough genetic screen was performed to identify genetic changes to compensate for the lack of PUFAs. The newly isolated suppressor mutations that compensated for FAT-2 growth defects included intergenic suppressors in the fat-2 gene, as well as constitutive mutations in the hypoxia sensing pathway components EGL-9 and HIF-1, and loss of function mutations in ftn-2, a gene encoding the iron storage protein ferritin. Taken together, these mutations lead to the model that increased intracellular iron, an essential cofactor for fatty acid desaturases, allows the minimally functional FAT-2(wa17) enzyme to be more active, resulting in increased desaturation and increased PUFA synthesis.

      Strengths:

      (1) This study provides new information further characterizing fat-2 mutants. The authors measured increased rigidity of membranes compared to wild type worms, however this rigidity is not able to be rescued with other fluidity treatments such as detergent or mutants. Rescue was only achieved with polyunsaturated fatty acid supplementation.<br /> (2) A very thorough genetic suppressor screen was performed. In addition to some internal fat-2 compensatory mutations, the only changes in pathways identified that are capable of compensating for deficient PUFA synthesis was the hypoxia pathway and the iron storage protein ferritin. Suppressor mutations included an egl-9 mutation that constitutively activates HIF-1, and Gain of function mutations in hif-1 that are dominant. This increased activity of HIF conferred by specific egl-9 and hif-1 mutations lead to decreased expression of ftn-2. Indeed, loss of ftn-2 leads to higher intracellular iron. The increased iron apparently makes the FAT-2 fatty acid desaturase enzyme more active, allowing for the production of more PUFAs.<br /> (3) The mutations isolated in the suppressor screen show that the only mutations able to compensate for lack of PUFAs were ones that increased PUFA synthesis by the defective FAT-2 desaturase, thus demonstrating the essential need for PUFAs that cannot be overcome by changes in other pathways. This is a very novel study, taking advantage of genetic analysis of C. elegans, and it confirms the observations in humans that certain essential PUFAs are required for growth and development.<br /> (4) Overall, the paper is well written, and the experiments were carried out carefully and thoroughly. The conclusions are well supported by the results.

      Weaknesses:

      Overall, there are not many weaknesses. The main one I noticed is that the lipidomic analysis shown in Figs 3C, 7C, S1 and S3. Whie these data are an essential part of the analysis and provide strong evidence for the conclusions of the study, it is unfortunate that the methods used did not enable the distinction between two 18:1 isomers. These two isomers of 18:1 are important in C. elegans biology, because one is a substrate for FAT-2 (18:1n-9, oleic acid) and the other is not (18:1n-7, cis vaccenic acid). Although rarer in mammals, cis-vaccenic acid is the most abundant fatty acid in C. elegans and is likely the most important structural MUFA. The measurement of these two isomers is not essential for the conclusions of the study, but the manuscript should include a comment about the abundance of oleic vs vaccenic acid in C. elegans (authors can find this information, even in the fat-2 mutant, in other publications of C. elegans fatty acid composition). Otherwise, readers who are not familiar with C. elegans might assume the 18:1 that is reported is likely to be mainly oleic acid, as is common in mammals.

      Other suggestions to authors to improve the paper:<br /> (1) The title could be less specific; it might be confusing to readers to include the allele name in the title.<br /> (2) There are two errors in the pathway depicted in Figure 1A. The16:0-16:1 desaturation can be performed by FAT-5, FAT-6, and FAT-7. The 18:0-18:1 desaturation can only be performed by FAT-6 and FAT-7

    1. Reviewer #1 (Public review):

      Bredenberg et al. aim to model some of the visual and neural effects of psychedelics via the Wake-Sleep algorithm. This is an interesting study with findings that go against certain mainstream ideas in psychedelic neuroscience (that I largely agree with). I cannot speak to the math in this manuscript, but it seems like quite a conceptual leap to set a parameter of the model in between wake and sleep and state that this is a proxy to acute psychedelic effects (point #20). My other concerns below are related to the review of the psychedelic literature:

      (1) Page 1, Introduction, "...they are agonists for the 5-HT2a serotonin receptor commonly expressed on the apical dendrites of cortical pyramidal neurons..." It is a bit redundant to say "5-HT2A serotonin receptor," as serotonin is already captured by its abbreviation (i.e., 5-HT).

      While psychedelic research has focused on 5-HT2A expression on cortical pyramidal cells, note that the 5-HT2A receptor is also expressed on interneurons in the medial temporal lobe (entorhinal cortex, hippocampus, and amygdala) with some estimates being >50% of these neurons (https://doi.org/10.1016/j.brainresbull.2011.11.006, https://doi.org/10.1007/s00221-013-3512-6, https://doi.org/10.7554/eLife.66960, https://doi.org/10.1016/j.mcn.2008.07.005, https://doi.org/10.1038/npp.2008.71, https://doi.org/10.1038/s41386-023-01744-8, https://doi.org/10.1016/j.brainres.2004.03.016, https://doi.org/10.1016/S0022-3565(24)37472-5, https://doi.org/10.1002/hipo.22611, https://doi.org/10.1016/j.neuron.2024.08.016). However, with ~1:4 ratio of inhibitory to excitatory neurons in the brain (https://doi.org/10.1101/2024.09.24.614724), this can make it seem as if 5-HT2A expression is negligible in the MTL. I think it might be important to mention these receptors, as this manuscript discusses replay.

      I see now that Figure 1 mentions that PV cells also express 5-HT2A receptors. This should probably be mentioned earlier.

      (2) Page 1, Introduction, "They have further been used for millennia as medicine and in religious rituals..." This might be a romanticization of psychedelics and indigenous groups, as anthropological evidence suggests that intentional psychedelic use might actually be more recent (see work by Manvir Singh and Andy Letcher).

      (3) When discussing oneirogens, it could be worth differentiating psychedelics from kappa opioid agonists such as ibogaine and salvinorin A, another class of hallucinogens that some refer to as "oneirogens" (similar to how "psychedelic" is the colloquial term for 5-HT2A agonists). Note that studies have found the effects of Salvia divinorum (which contains salvinorin A) to be described more similarly to dreams than psychedelics (https://doi.org/10.1007/s00213-011-2470-6). This makes me wonder why the present study is more applicable to 5-HT2A psychedelics than other kappa opioid agonists or other classes of hallucinogens (e.g., NMDA antagonists, muscarinic antagonists, GABAA agonists).

      (4) Page 2, Introduction, "Replay sequences have been shown to be important for learning during sleep [14, 15, 16, 17, 18]: we propose that mechanisms supporting replay-dependent learning during sleep are key to explaining the increases in plasticity caused by psychedelic drug administration." I'm not sure I follow the logic of this point. Dreams happen during REM sleep, whereas replay is most prominent during non-REM sleep. Moreover, while it's not clear what psychedelics do to hippocampal function, most evidence would suggest they impair it. As mentioned, most 5-HT2A receptors in the hippocampus seem to be on inhibitory neurons, and human and animal work finds that psychedelics impair hippocampal-dependent memory encoding (https://doi.org/10.1037/rev0000455, https://doi.org/10.1037/rev0000455, https://doi.org/10.3389/fnbeh.2014.00180, https://doi.org/10.1002/hipo.22712). One study even found that psilocin impairs hippocampal-dependent memory retrieval (https://doi.org/10.3389/fnbeh.2014.00180). Note that this is all in reference to the acute effects (psychedelics may post-acutely enhance hippocampal-dependent memory, https://doi.org/10.1007/s40265-024-02106-4).

      (5) Page 2, Introduction, "In total, our model of the functional effect of psychedelics on pyramidal neurons could provide a explanation for the perceptual psychedelic experience in terms of learning mechanisms for consolidation during sleep..." In contrast to my previous point, I think this could be possible. Three datasets have found that psychedelics may enhance cortical-dependent memory encoding (i.e., familiarity; https://doi.org/10.1037/rev0000455, https://doi.org/10.1037/rev0000455), and two studies found that post-encoding administration of psychedelics retroactively enhanced memory that may be less hippocampal-dependent/more cortical-dependent (https://doi.org/10.1016/j.neuropharm.2012.06.007, https://doi.org/10.1016/j.euroneuro.2022.01.114). Moreover, and as mentioned below, 5 studies have found decoupling between the hippocampus and the cortex (https://doi.org/10.3389/fnhum.2014.00020, https://doi.org/10.1002/hbm.22833, https://doi.org/10.1016/j.celrep.2021.109714, https://doi.org/10.1162/netn_a_00349, https://doi.org/10.1038/s41586-024-07624-5), something potentially also observed during REM sleep that is thought to support consolidation (https://doi.org/10.1073/pnas.2123432119). These findings should probably be discussed.

      (6) Page 2, Introduction, "In this work, we show that within a neural network trained via Wake-Sleep, it is possible to model the action of classical psychedelics (i.e. 5-HT2a receptor agonism)..." Note that 5-HT2A agonism alone is not sufficient to explain the effects of psychedelics, given that there are 5-HT2A agonists that are non-hallucinogenic (e.g., lisuride).

      (7) Page 2, Introduction, "...by shifting the balance during the wake state from the bottom-up pathways to the top-down pathways, thereby making the 'wake' network states more 'dream-like'." I could have included this in the previous point, but I felt that this idea deserved its own point. There has been a rather dogmatic assertion that psychedelics diminish top-down processing and/or enhance bottom-up processing, and I appreciate that the authors have not accepted this as fact. However, because this is an unfortunately prominent idea, I think it ought to be fleshed out more by first mentioning that it's one of the tenets of REBUS. REBUS has become a popular model of psychedelic drug action, but it's largely unfalsifiable (it's based on two unfalsifiable models, predictive processing and integrated information theory), so the findings from this study could tighten it up a bit. Second, there have now been a handful of studies that have attempted to study directionality in information flow under psychedelics, and the findings are rather mixed including increased bottom-up/decreased top-down effects (https://doi.org/10.7554/eLife.59784, https://doi.org/10.1073/pnas.1815129116; note that the latter "bottom-up" effect involves subcortical-cortical connections in which it's less clear what's actually "higher-/lower-level"), increased top-down/decreased bottom-up effects (https://doi.org/10.1038/s41380-024-02632-3, https://doi.org/10.1016/j.euroneuro.2016.03.018), or both (https://doi.org/10.1016/j.neuroimage.2019.116462, https://doi.org/10.1016/j.neuropharm.2017.10.039), though most of these studies are aggregating across largely inhomogeneous states (i.e., resting-state). Lastly, and somewhat problematically, facilitated top-down processing is also an idea proposed in psychosis that's based partially on findings with acute ketamine administration (note that all hallucinations to some degree might rely on top-down facilitation, as a hallucination involves a high-level concept that impinges on lower-level sensory areas; see work by Phil Corlett). While psychosis and the effects of ketamine have some similarities with psychedelics, there are certainly differences, and I think the goal of this manuscript is to uniquely describe 5-HT2A psychedelics (again, I'm left wondering why tweaking alpha in the Wake-Sleep algorithm is any more applicable to psychedelics than other hallucinogenic conditions).

      (8) Figure 2 equates alpha with a "psychedelic dose," but this is a bit misleading, as neither the algorithm nor an individual was administered a psychedelic. Alpha is instead a hypothetical proxy for a psychedelic dose. Moreover, if the model were recapitulating the effects of psychedelics, shouldn't these images look more psychedelic as alpha increases (e.g., they may look like images put through the DeepDream algorithm).

      (9) Page 11, Methods, "...and the gate α ensures that learning only occurs during sleep mode... The (1 − α) gate in this case ensures that plasticity only occurs during the Wake mode." Much of the math escapes me, so perhaps I'm misunderstanding these statements, but learning and plasticity certainly happen during both wake and sleep, making me wonder what is meant by these statements. Moreover, if plasticity is simply neural changes, couldn't plasticity be synonymous with neural learning? Perhaps plasticity and learning are meant to refer to different types of neural changes. It might be worth clarifying this, as a general problem in psychedelic research is that psychedelics are described as facilitating plasticity when brains are changing at every moment (hence not experiencing every moment as the same), and psychedelics don't impact all forms of plasticity equally. For example, psychedelics may not necessarily enhance neurogenesis or the addition of certain receptor types, and they impair certain forms of learning (i.e., episodic memory encoding). What is typically meant by plasticity enhancements induced by psychedelics (and where there's the most evidence) is dendritic plasticity (i.e., the growth of dendrites and spines). Whatever is meant by "plasticity" should be clarified in its first instance in this manuscript.

      (10) Page 12, Methods, "During training, neural network activity is either dominated entirely by bottom-up inputs (Wake, α = 0) or by top-down inputs (Sleep, α = 1)." Again, I could be misunderstanding the mathematical formulation, but top-down inputs operate during wake, and bottom-up inputs can operate during sleep (people can wake up or even incorporate noise from their environments into sleep.

      (11) Page 4, Results, "Thus, we can capture the core idea behind the oneirogen hypothesis using the Wake-Sleep algorithm, by postulating that the bottom-up basal synapses are predominantly driving neural activity during the Wake phase (when α is low)." However, several pieces of evidence (and the first circuit model of psychedelic drug action) suggest that psychedelics enhance functional connectivity and potentially even effective connectivity from the thalamus to the cortex (https://doi.org/10.1093/brain/awab406). Note that psychedelics may not equally impact all subcortical structures. REBUS proposes the opposite of the current study, that psychedelics facilitate bottom-up information flow, with one of the few explicit predictions being that psychedelics should facilitate information flow from the hippocampus to the default mode network. However, as mentioned earlier, 5 studies have found that psychedelics diminish functional connectivity between the hippocampus and cortex (including the DMN but also V1).

      (12) Page 4, Results, "...and have an excitatory effect that positively modulates glutamatergic transmission..." Note that this may not be brainwide. While psychedelics were found to increase glutamatergic transmission in the cortex, they were also found to decrease hippocampal glutamate (consistent with inhibition of the hippocampus, https://doi.org/10.1038/s41386-020-0718-8).

      (13) Page 5, "...which are similar to the 'breathing' and 'rippling' phenomena reported by psychedelic drug users at low doses..." Although it's sometimes unclear what is meant by "low doses," the breathing/rippling effect of psychedelics occurs at moderate and high doses as well.

      (14) I watched the videos, and it's hard for me to say there was some stark resemblance to psychedelic imagery. In contrast, for example, when the DeepDream algorithm came out, it did seem to capture something quite psychedelic.

      (15) Page 5, "This form of strongly correlated tuning has been observed in both cortex and the hippocampus." If this has been observed under non-psychedelic conditions, what does this tell us about this supposed model of psychedelics?

      (16) Page 6, with regards to neural variability, "...but whether this phenomenon [increased variability] is general across tasks and cortical areas remains to be seen." First, is variability here measured as variance? In fMRI datasets that have been used to support the Entropic Brain Hypothesis, note that variance tends to decrease, though certain measures of entropy increase (e.g., Figure 4A here https://doi.org/10.1073/pnas.1518377113 shows global variance decreases, and this reanalysis of those data https://doi.org/10.1002/hbm.23234 finds some entropy increases). Thus, variance and entropy should not be confused (in theory, one could cycle through several more brain states that are however, similar to each other, which would produce more entropy with decreased variance). Second, and perhaps more problematically for the EBH, is that the entropy effects of psychedelics completely disappear when one does a task, and unfortunately, the authors of these findings have misinterpreted them. What they'll say is that engaging in boring cognitive tasks or watching a video decreases entropy under psychedelics, but what you can see in Figure 1b of https://doi.org/10.1021/acschemneuro.3c00289 and Figure 4b of https://doi.org/10.1038/s41586-024-07624-5 is that entropy actually increases under sober conditions when you do a task. That is, it's a rather boring finding. Essentially, when resting in a scanner while sober, many may actually rest (including falling asleep, especially when subjects are asked to keep their eyes closed), and if you perform a task, brain activity should become more complex relative to doing nothing/falling asleep. When under a psychedelic, one can't fall asleep and thus, there's less change (though note that both of the above studies found numerical increases when performing tasks). Lastly, again I should note that the findings of the present study actually go against EBH/REBUS, given that the findings are increased top-down effects when EBH/REBUS predicts decreased top-down/increased bottom-up effects.

      (17) Page 6, "Because psychedelic drug administration increases influence of apical dendritic inputs on neural activity in our model, we found that silencing apical dendritic activity reduced across stimulus neural variability more as the psychedelic drug dose increases." I again want to point out that alpha is not the equivalent of a psychedelic dose here, but rather a parameter in the model that is being proposed as a proxy.

      (18) Page 8, "Experimentally, plasticity dynamics which could, theoretically, minimize such a prediction error have been observed in cortex [66, 67], and it has also been proposed that behavioral timescale plasticity in the hippocampus could subserve a similar function [68]. We found that plasticity rules of this kind induce strong correlations between inputs to the apical and basal dendritic compartments of pyramidal neurons, which have been observed in the hippocampus and cortex [55, 56]." Note that the plasticity effects of psychedelics are sometimes not observed in the hippocampus or are even observed as decreases (reviewed in https://doi.org/10.1038/s41386-022-01389-z).

      (19) Page 9, as is mentioned, REBUS proposes that there should be a decrease in top-down effects under psychedelics, which goes against what is found here, but as I describe above, the effects of psychedelics on various measures of directionality have been quite mixed.

      (20) Unless I'm misunderstanding something, it seems to be a bit of a jump to infer that simply changing alpha in your model is akin to psychedelic dosing. Perhaps if the model implemented biologically plausible 5-HT2A expression and/or its behavior were constrained by common features of a psychedelic experience (e.g., fractal-like visuals imposed onto perception, inability to fall asleep, etc.), I'd be more inclined to see the parallels between alpha and psychedelics dosing. However, it would still need to recapitulate unique effects of psychedelics (e.g., impairments in hippocampal-dependent memory with sparing/facilitation of cortical memory). At the moment, it seems like whatever the model is doing is applicable to any hallucinogenic drug or even psychosis.

    2. Author response:

      We thank the reviewers for the valuable and constructive reviews. Thanks to these, we believe the article will be considerably improved. We have organized our response to address points that are relevant to both reviewers first, after which we address the unique concerns of each individual reviewer separately. We briefly paraphrase each concern and provide comments for clarification, outlining the precise changes that we will make to the text.

      Common Concerns (Reviewer 1 & Reviewer 2):

      Can you clarify how NREM and REM sleep relate to the oneirogen hypothesis?

      Within the submission draft we tried to stay agnostic as to whether mechanistically similar replay events occur during NREM or REM sleep; however, upon a more thorough literature review, we think that there is moderately greater evidence in favor of Wake-Sleep-type replay occurring during REM sleep which is related to classical psychedelic drug mechanisms of action.

      First, we should clarify that replay has been observed during both REM and NREM sleep, and dreams have been documented during both sleep stages, though the characteristics of dreams differ across stages, with NREM dreams being more closely tied to recent episodic experience and REM dreams being more bizarre/hallucinatory (see Stickgold et al., 2001 for a review). Replay during sleep has been studied most thoroughly during NREM sharp-wave ripple events, in which significant cortical-hippocampal coupling has been observed (Ji & Wilson, 2007). However, it is critical to note that the quantification methods used to identify replay events in the hippocampal literature usually focus on identifying what we term ‘episodic replay,’ which involves a near-identical recapitulation of neural trajectories that were recently experienced during waking experimental recordings (Tingley & Peyrach, 2020). In contrast, our model focuses on ‘generative replay,’ where one expects only a statistically similar reproduction of neural activity, without any particular bias towards recent or experimentally controlled experience. This latter form of replay may look closer to the ‘reactivation’ observed in cortex by many studies (e.g. Nguyen et al., 2024), where correlation structures of neural activity similar to those observed during stimulus-driven experience are recapitulated. Under experimental conditions in which an animal is experiencing highly stereotyped activity repeatedly, over extended periods of time, these two forms of replay may be difficult to dissociate.

      Interestingly, though NREM replay has been shown to couple hippocampal and cortical activity, a similar study in waking animals administered psychedelics found hippocampal replay without any obvious coupling to cortical activity (Domenico et al., 2021). This could be because the coupling was not strong enough to produce full trajectories in the cortex (psychedelic administration did not increase ‘alpha’ enough), and that a causal manipulation of apical/basal influence in the cortex may be necessary to observe the increased coupling. Alternatively, as Reviewer 1 noted, it may be that psychedelics induce a form of hippocampus-decoupled replay, as one would expect from the REM stage of a recently proposed complementary learning systems model (Singh et al., 2022). 

      Evidence in favor of a similarity between the mechanism of action of classical psychedelics and the mechanism of action of memory consolidation/learning during REM sleep is actually quite strong. In particular, studies have shown that REM sleep increases the activity of soma-targeting parvalbumin (PV) interneurons and decreases the activity of apical dendrite-targeting somatostatin (SOM) interneurons (Niethard et al., 2021), that this shift in balance is controlled by higher-order thalamic nuclei, and that this shift in balance is critical for synaptic consolidation of both monocular deprivation effects in early visual cortex (Zhou et al., 2020) and for the consolidation of auditory fear conditioning in the dorsal prefrontal cortex (Aime et al., 2022). These last studies were not discussed in the present manuscript–we will add them, in addition to a more nuanced description of the evidence connecting our model to NREM and REM replay.

      Can you explain how synaptic plasticity induced by psychedelics within your model relates to learning at a behavioral level?

      While the Wake-Sleep algorithm is a useful model for unsupervised statistical learning, it is not a model of reward or fear-based conditioning, which likely occur via different mechanisms in the brain (e.g. dopamine-dependent reinforcement learning or serotonin-dependent emotional learning). The Wake-Sleep algorithm is a ‘normative plasticity algorithm,’ that connects synaptic plasticity to the formation of structured neural representations, but it is not the case that all synaptic plasticity induced by psychedelic administration within our model should induce beneficial learning effects. According to the Wake-Sleep algorithm, plasticity at apical synapses is enhanced during the Wake phase, and plasticity at basal synapses is enhanced during the Sleep phase; under the oneirogen hypothesis, hallucinatory conditions (increased ‘alpha’) cause an increase in plasticity at both apical and basal sites. Because neural activity is in a fundamentally aberrant state when ‘alpha’ is increased, there are no theoretical guarantees that plasticity will improve performance on any objective: psychedelic-induced plasticity within our model could perhaps better be thought of as ‘noise’ that may have a positive or negative effect depending on the context.

      In particular, such ‘noise’ may be beneficial for individuals or networks whose synapses have become locked in a suboptimal local minimum. The addition of large amounts of random plasticity could allow a system to extricate itself from such local minima over subsequent learning (or with careful selection of stimuli during psychedelic experience), similar to simulated annealing optimization approaches. If our model were fully validated, this view of psychedelic-induced plasticity as ‘noise’ could have relevance for efforts to alleviate the adverse effects of PTSD, early life trauma, or sensory deprivation; it may also provide a cautionary note against repeated use of psychedelic drugs within a short time frame, as the plasticity changes induced by psychedelic administration under our model are not guaranteed to be good or useful in-and-of themselves without subsequent re-learning and compensation.

      We should also note that we have deliberately avoided connecting the oneirogen hypothesis model to fear extinction experimental results that have been observed through recordings of the hippocampus or the amygdala (Bombardi & Giovanni, 2013; Jiang et al., 2009; Kelly et al., 2024; Tiwari et al., 2024). Both regions receive extensive innervation directly from serotonergic synapses originating in the dorsal raphe nucleus, which have been shown to play an important role in emotional learning (Lesch & Waider, 2012); because classical psychedelics may play a more direct role in modulating this serotonergic innervation, it is possible that fear conditioning results (in addition to the anxiolytic effects of psychedelics) cannot be attributed to a shift in balance between apical and basal synapses induced by psychedelic administration. We will provide a more detailed review of these results in the text, as well as more clarity regarding their relation to our model.

      Reviewer 1 Concerns:

      Is it reasonable to assign a scalar parameter ‘alpha’ to the effects of classical psychedelics? And is your proposed mechanism of action unique to classical psychedelics? E.g. Could this idea also apply to kappa opioid agonists, ketamine, or the neural mechanisms of hallucination disorders?

      We will clarify that within our model ‘alpha’ is a parameter that reflects the balance between apical and basal synapses in determining the activity of neurons in the network. For the sake of simplicity we used a single ‘alpha’ parameter, but realistically, each neuron would have its own ‘alpha’ parameter, and different layers or individual neurons could be affected differentially by the administration of any particular drug; therefore, our scalar ‘alpha’ value can be thought of as a mean parameter for all neurons, disregarding heterogeneity across individual neurons.

      There are many different mechanisms that could theoretically affect this ‘alpha’ parameter, including: 5-HT2a receptor agonism, kappa opioid receptor binding, ketamine administration, or possibly the effects of genetic mutations underlying the pathophysiology of complex developmental hallucination disorders. We focused exclusively on 5-HT2a receptor agonism for this study because the mechanism is comparatively simple and extensively characterized, but similar mechanisms may well be responsible for the hallucinatory symptoms of a variety of drugs and disorders.

      Can you clarify the role of 5-HT2a receptor expression on interneurons within your model?

      While we mostly focused on the effects of 5-HT2a receptors on the apical dendrites of pyramidal neurons, these receptors are also expressed on soma-targeting parvalbumin (PV) interneurons. This expression on PV interneurons is consistent with our proposed psychedelic mechanism of action, because it could lead to a coordinated decrease in the influence of somatic and proximal dendritic inputs while increasing the influence of apical dendritic inputs. We will elaborate on this point, and will move the discussion earlier in the text.

      Discussions of indigenous use of psychedelics over millenia may amount to over-romanticization.

      We will take great care to conduct a more thorough literature review to reevaluate our statement regarding indigenous psychedelic use (including the citations you suggested), and will either provide a more careful statement or remove this discussion from our introduction entirely, as it has little bearing on the rest of the text. The Ethics Statement will also be modified accordingly.

      You isolate the 5-HT2a agonism as the mechanism of action underlying ‘alpha’ in your model, but there exist 5-HT2a agonists that do not have hallucinatory effects (e.g. lisuride). How do you explain this?

      Lisuride has much-reduced hallucinatory effects compared to other psychedelic drugs at clinical doses (though it does indeed induce hallucinations at high doses; Marona-Lewicka et al., 2002), and we should note that serotonin (5-HT) itself is pervasive in the cortex without inducing hallucinatory effects during natural function. Similarly, MDMA is a partial agonist for 5-HT2a receptors, but it has much-reduced perceptual hallucination effects relative to classical psychedelics (Green et al., 2003) in addition to many other effects not induced by classical psychedelics.

      Therefore, while we argue that 5-HT2a agonism induces an increase in influence of apical dendritic compartments and a decrease in influence of basal/somatic compartments, and that this change induces hallucinations, we also note that there are many other factors that control whether or not hallucinations are ultimately produced, so that not all 5-HT2a agonists are hallucinogenic. We will discuss two such factors in our revision: 5-HT receptor binding affinity and cellular membrane permeability.

      Importantly, many 5-HT2a receptor agonists are also 5-HT1a receptor agonists (e.g. serotonin itself and lisuride), while MDMA has also been shown to increase serotonin, norepinephrine, and dopamine release (Green et al., 2003). While 5-HT2a receptor agonism has been shown to reduce sensory stimulus responses (Michaiel et al., 2019), 5-HT1a receptor agonism inhibits spontaneous cortical activity (Azimi et al., 2020); thus one might expect the net effect of administering serotonin or a nonselective 5-HT receptor agonist to be widespread inhibition of a circuit, as has been observed in visual cortex (Azimi et al., 2020). Therefore, selective 5-HT2a agonism is critical for the induction of hallucinations according to our model, though any intervention that jointly excites pyramidal neurons’ apical dendrites and inhibits their basal/somatic compartments across a broad enough area of cortex would be predicted to have a similar effect. Lisuride has a much higher binding affinity for 5-HT1a receptors than, for instance, LSD (Marona-Lewicka et al., 2002).

      Secondly, it has recently been shown that both the head-twitch effect (a coarse behavioral readout of hallucinations in animals) and the plasticity effects of psychedelics are abolished when administering 5-HT2a agonists that are impermeable to the cellular membrane because of high polarity, and that these effects can be rescued by temporarily rendering the cellular membrane permeable (Vargas et al., 2023). This suggests that the critical hallucinatory effects of psychedelics (apical excitation according to our model) may be mediated by intracellular 5-HT2a receptors. Notably, serotonin itself is not membrane permeable in the cortex.

      Therefore, either of these two properties could play a role in whether a given 5-HT2a agonist induces hallucinatory effects. We will provide a considerably extended discussion of these nuances in our revision.

      Your model proposes that an increase in top-down influence on neural activity underlies the hallucinatory effects of psychedelics. How do you explain experimental results that show increases in bottom-up functional connectivity (either from early sensory areas or the thalamus)?

      Firstly, we should note that our proposed increase in top-down influence is a causal, biophysical property, not necessarily a statistical/correlative one. As such, we will stress that the best way to test our model is via direct intervention in cortical microcircuitry, as opposed to correlative approaches taken by most fMRI studies, which have shown mixed results with regard to this particular question. Correlative approaches can be misleading due to dense recurrent coupling in the system, and due to the coarse temporal and spatial resolution provided by noninvasive recording technologies (changes in statistical/functional connectivity do not necessarily correspond to changes in causal/mechanistic connectivity, i.e. correlation does not imply causation).

      There are two experimental results that appear to contradict our hypothesis that deserve special consideration in our revision. The first shows an increase in directional thalamic influence on the distributed cortical networks after psychedelic administration (Preller et al., 2018). To explain this, we note that this study does not distinguish between lower-order sensory thalamic nuclei (e.g. the lateral and medial geniculate nuclei receiving visual and auditory stimuli respectively) and the higher-order thalamic nuclei that participate in thalamocortical connectivity loops (Whyte et al., 2024). Subsequent more fine-grained studies have noted an increase in influence of higher order thalamic nuclei on the cortex (Pizzi et al., 2023; Gaddis et al., 2022), and in fact extensive causal intervention research has shown that classical psychedelics (and 5-HT2a agonism) decrease the influence of incoming sensory stimuli on the activity of early sensory cortical areas, indicating decoupling from the sensory thalamus (Evarts et al., 1955; Azimi et al., 2020; Michaiel et al. 2019). The increased influence of higher-order thalamic nuclei is consistent with both the cortico-striatal-thalamo-cortical (CTSC) model of psychedelic action as well as the oneirogen hypothesis, since higher-order thalamic inputs modulate the apical dendrites of pyramidal neurons in cortex (Whyte et al., 2024).

      The second experimental result notes that DMT induces traveling waves during resting state activity that propagate from early visual cortex to deeper cortical layers (Alamia et al., 2020). There are several possibilities that could explain this phenomenon: 1) it could be due to the aforementioned difficulties associated with directed functional connectivity analyses, 2) it could be due to a possible high binding affinity for DMT in the visual cortex relative to other brain areas, or 3) it could be due to increases in apical influence on activity caused by local recurrent connectivity within the visual cortex which, in the absence of sensory input, could lead to propagation of neural activity from the visual cortex to the rest of the brain. This last possibility is closest to the model proposed by (Ermentrout & Cowan, 1979), and which we believe would be best explained within our framework by a topographically connected recurrent network architecture trained on video data; a potentially fruitful direction for future research.

      Shouldn’t the hallucinations generated by your model look more ‘psychedelic,’ like those produced by the DeepDream algorithm?

      We believe that the differences in hallucination visualization quality between our algorithm and DeepDream are mostly due to differences in the scale and power of the models used across these two studies. We are confident that with more resources (and potentially theoretical innovations to improve the Wake-Sleep algorithm’s performance) the produced hallucination visualizations could become more realistic, but we believe this falls outside the scope of the present study.

      We note that more powerful generative models trained with backpropagation are able to produce surreal images of comparable quality (Rezende et al., 2014; Goodfellow et al., 2020; Vahdat & Kautz, 2020), though these have not yet been used as a model of psychedelic hallucinations. However, the DeepDream model operates on top of large pretrained image processing models, and does not provide a biologically mechanistic/testable interpretation of its hallucination effects. When training smaller models with a local synaptic plasticity rule (as opposed to backpropagation), the hallucination effects are less visually striking due to the reduced quality of our trained generative model, though they are still strongly tied to the statistics of sensory inputs, as quantified by our correlation similarity metric (Fig. 5b). We will provide a more detailed explanation of this phenomenon when we discuss our model limitations in our revised manuscript.

      Your model assumes domination by entirely bottom-up activity during the ‘wake’ phase, and domination entirely by top-down activity during ‘sleep,’ despite experimental evidence indicating that a mixture of top-down and bottom-up inputs influence neural activity during both stages in the brain. How do you explain this?

      Our use of the Wake-Sleep algorithm, in which top-down inputs (Sleep) or bottom-up inputs (Wake) dominate network activity is an over-simplification made within our model for computational and theoretical reasons. Models that receive a mixture of top-down and bottom-up inputs during ‘Wake’ activity do exist (in particular the closely related Boltzmann machine (Ackley et al., 1985)), but these models are considerably more computationally costly to train due to a need to run extensive recurrent network relaxation dynamics for each input stimulus. Further, these models do not generalize as cleanly to processing temporal inputs. For this reason, we focused on the Wake-Sleep algorithm, at the cost of some biological realism, though we note that our model should certainly be extended to support mixed apical-basal waking regimes. We will make sure to discuss this in our ‘Model Limitations’ section.

      Your model proposes that 5-HT2a agonism enhances glutamatergic transmission, but this is not true in the hippocampus, which shows decreases in glutamate after psychedelic administration.

      We should note that our model suggests only compartment specific increases in glutamatergic transmission; as such, our model does not predict any particular directionality for measures of glutamatergic transmission that includes signaling at both apical and basal compartments in aggregate, as was measured in the provided study (Mason et al., 2020).

      You claim that your model is consistent with the Entropic Brain theory, but you report increases in variance, not entropy. In fact, it has been shown that variance decreases while entropy increases under psychedelic administration. How do you explain this discrepancy?

      Unfortunately, ‘entropy’ and ‘variance’ are heavily overloaded terms in the noninvasive imaging literature, and the particularities of the method employed can exert a strong influence on the reported effects. The reduction in variance reported by (Carhart-Harris et al., 2016) is a very particular measure: they are reporting the variance of resting state synchronous activity, averaged across a functional subnetwork that spans many voxels; as such, the reduction in variance in this case is a reduction in broad, synchronous activity. We do not have any resting state synchronous activity in our network due to the simplified nature of our model (particularly an absence of recurrent temporal dynamics), so we see no reduction in variance in our model due to these effects.

      Other studies estimate ‘entropy’ or network state disorder via three different methods that we have been able to identify. 1) (Carhart-Harris et al., 2014) uses a different measure of variance: in this case, they subtract out synchronous activity within functional subnetworks, and calculate variability across units in the network. This measure reports increases in variance (Fig. 6), and is the closest measure to the one we employ in this study. 2) (Lebedev et al., 2016) uses sample entropy, which is a measure of temporal sequence predictability. It is specifically designed to disregard highly predictable signals, and so one might imagine that it is a measure that is robust to shared synchronous activity (e.g. resting state oscillations). 3) (Mediano et al., 2024) uses Lempel-Ziv complexity, which is, similar to sample entropy, a measure of sequence diversity; in this case the signal is binarized before calculation, which makes this method considerably different from ours. All three of the preceding methods report increases in sequence diversity, in agreement with our quantification method. Our strongest explanation for why the variance calculation in (Carhart-Harris et al., 2016) produces a variance reduction is therefore due to a reduction in low-rank synchronous activity in subnetworks during resting state.

      As for whether the entropy increase is meaningful: we share Reviewer 1’s concern that increases in entropy could simply be due to a higher degree of cognitive engagement during resting state recordings, due to the presence of sensory hallucinations or due to an inability to fall asleep. This could explain why entropy increases are much more minimal relative to non-hallucinating conditions during audiovisual task performance (Siegel et al., 2024; Mediano et al., 2024). However, we can say that our model is consistent with the Entropic Brain Theory without including any form of ‘cognitive processing’: we observe increases in variability during resting state in our model, but we observe highly similar distributions of activity when averaging over a wide variety of sensory stimulus presentations (Fig. 5b-c). This is because variability in our model is not due to unstructured noise: it corresponds to an exploration of network states that would ordinarily be visited by some stimulus. Therefore, when averaging across a wide variety of stimuli, the distribution of network states under hallucinating or non-hallucinating conditions should be highly similar.

      One final point of clarification: here we are distinguishing Entropic Brain Theory from the REBUS model–the oneirogen hypothesis is consistent with the increase in entropy observed experimentally, but in our model this entropy increase is not due to increased influence of bottom-up inputs (it is due instead to an increase in top-down influence). Therefore, one could view the oneirogen hypothesis as consistent with EBT, but inconsistent with REBUS.

      You relate your plasticity rule to behavioral-timescale plasticity (BTSP) in the hippocampus, but plasticity has been shown to be reduced in the hippocampus after psychedelic administration. Could you elaborate on this connection?

      When we were establishing a connection between our ‘Wake-Sleep’ plasticity rule and BTSP learning, the intended connection was exclusively to the mathematical form of the plasticity rule, in which activity in the apical dendrites of pyramidal neurons functions as an instructive signal for plasticity in basal synapses (and vice versa): we will clarify this in the text. Similarly, we point out that such a plasticity rule tends to result in correlated tuning between apical and basal dendritic compartments, which has been observed in hippocampus and cortex: this is intended as a sanity check of our mapping of the Wake-Sleep algorithm to cortical microcircuitry, and has limited further bearing on the effects of psychedelics specifically.

      Reduction in plasticity in the hippocampus after psychedelic administration could be due to a complementary learning systems-type model, in which the hippocampus becomes partly decoupled from the cortex during REM sleep (Singh et al., 2022); were this to be the case, it would not be incompatible with our model, which is mostly focused on the cortex. Notably, potentiating 5HT-2a receptors in the ventral hippocampus does not induce the head-twitch response, though it does produce anxiolytic effects (Tiwari et al., 2024), indicating that the hallucinatory and anxiolytic effects of classical psychedelics may be partly decoupled. 

      Reviewer 2 Concerns:

      Could you provide visualizations of the ‘ripple’ phenomenon that you’re referring to?

      We will do this! For now, you can get a decent understanding of what the ‘ripple effect’ looks like from the ‘eyes closed’ hallucination condition for networks trained on CIFAR10 (Fig. 2d). The ripple effect that we are referring to is very similar, except it is superimposed on a naturalistic image under ordinary viewing conditions; to give a higher quality visualization of the ripple phenomenon itself, we will subtract out the static contribution of the image itself, leaving only the ripple phenomenon.

      Could you provide a more nuanced description of alternative roles for top-down feedback, beyond being used exclusively for learning as depicted in your model?

      For the sake of simplicity, we only treat top-down inputs in our model as a source of an instructive teaching signal, the originator of generative replay events during the Sleep phase, and as the mechanism of hallucination generation. However, as discussed in a response to a previous question, in the cortex pyramidal neurons receive and respond to a mixture of top-down and bottom-up processing.

      There are a variety of theories for what role top-down inputs could play in determining network activity. To name several, top-down input could function as: 1) a denoising/pattern completion signal (Kadkhodaie & Simoncelli, 2021), 2) a feedback control signal (Podlaski & Machens, 2020), 3) an attention signal (Lindsay, 2020), 4) ordinary inputs for dynamic recurrent processing that play no specialized role distinct from bottom-up or lateral inputs except to provide inputs from higher-order association areas or other sensory modalities (Kar et al., 2019; Tugsbayar et al., 2025). Though our model does not include these features, they are perfectly consistent with our approach.

      In particular, denoising/pattern completion signals in the predictive coding framework (closely related to the Wake-Sleep algorithm) also play a role as an instructive learning signal (Salvatori et al., 2021); and top-down control signals can play a similar role in some models (Gilra & Gerstner, 2017; Meulemans et al., 2021). Thus, options 1 and 2 are heavily overlapping with our approach, and are a natural consequence of many biologically plausible learning algorithms that minimize a variational free energy loss (Rao & Ballard, 1997; Ackley et al., 1985). Similarly, top-down attentional signals can exist alongside top-down learning signals, and some models have argued that such signals can be heavily overlapping or mutually interchangeable (Roelfsema & van Ooyen, 2005). Lastly, generic recurrent connectivity (from any source) can be incorporated into the Wake-Sleep algorithm (Dayan & Hinton, 1996), though we avoided doing this in the present study due to an absence of empirical architecture exploration in the literature and the computational complexity associated with training on time series data.

      To conclude, there are a variety of alternative functions proposed for top-down inputs onto pyramidal neurons in the cortex, and we view these additional features as mutually compatible with our approach; for simplicity we did not include them in our model, but we believe that these features are unlikely to interfere with our testable predictions or empirical results.

    1. Reviewer #1 (Public review):

      Summary:

      The paper presents a novel method for RSA, called trial-level RSA (tRSA). The method first constructs a trial x trial representation dissimilarity matrix using correlation distances, assuming that (as in the empirical example) each trial has a unique stimulus. Whereas "classical RSA" correlates the entire upper triangular matrix of the RDM / RSM to a model RDM / RSM, tRSA first calculates the correlation to the model RDM per row, and then averages these values. The paper claims that tRSA has increased sensitivity and greater flexibility than classical RSA.

      Strengths & Weaknesses:

      I have to admit that it took a few hours of intense work to understand this paper and to even figure out where the authors were coming from. The problem setting, nomenclature, and simulation methods presented in this paper do not conform to the notation common in the field, are often contradictory, and are usually hard to understand. Most importantly, the problem that the paper is trying to solve seems to me to be quite specific to the particular memory study in question, and is very different from the normal setting of model-comparative RSA that I (and I think other readers) may be more familiar with.

      Main issues:

      (1) The definition of "classical RSA" that the authors are using is very narrow. The group around Niko Kriegeskorte has developed RSA over the last 10 years, addressing many of the perceived limitations of the technique. For example, cross-validated distance measures (Walther et al. 2016; Nili et al. 2014; Diedrichsen et al. 2021) effectively deal with an uneven number of trials per condition and unequal amounts of measurement noise across trials. Different RDM comparators (Diedrichsen et al. 2021) and statistical methods for generalization across stimuli (Schütt et al. 2023) have been developed, addressing shortcomings in sensitivity. Finally, both a Bayesian variant of RSA (Pattern component modelling, (Diedrichsen, Yokoi, and Arbuckle 2018) and an encoding model (Naselaris et al. 2011) can effectively deal with continuous variables or features across time points or trials in a framework that is very related to RSA (Diedrichsen and Kriegeskorte 2017). The author may not consider these newer developments to be classical, but they are in common use and certainly provide the solution to the problems raised in this paper in the setting of model-comparative RSA in which there is more than one repetition per stimulus.

      (2) The stated problem of the paper is to estimate "representational strength" in different regions or conditions. With this, the authors define the correlation of the brain RDM with a model RDM. This metric conflates a number of factors, namely the variances of the stimulus-specific patterns, the variance of the noise, the true differences between different dissimilarities, and the match between the assumed model and the data-generating model. It took me a long time to figure out that the authors are trying to solve a quite different problem in a quite different setting from the model-comparative approach to RSA that I would consider "classical" (Diedrichsen et al. 2021; Diedrichsen and Kriegeskorte 2017). In this approach, one is trying to test whether local activity patterns are better explained by representation model A or model B, and to estimate the degree to which the representation can be fully explained. In this framework, it is common practice to measure each stimulus at least 2 times, to be able to estimate the variance of noise patterns and the variance of signal patterns directly. Using this setting, I would define 'representational strength" very differently from the authors. Assume (using LaTeX notation) that the activity patterns $y_j,n$ for stimulus j, measurement n, are composed of a true stimulus-related pattern ($u_j$) and a trial-specific noise pattern ($e_j,n$). As a measure of the strength of representation (or pattern), I would use an unbiased estimate of the variance of the true stimulus-specific patterns across voxels and stimuli ($\sigma^2_{u}$). This estimator can be obtained by correlating patterns of the same stimuli across repeated measures, or equivalently, by averaging the cross-validated Euclidean distances (or with spatial prewhitening, Mahalanobis distances) across all stimulus pairs. In contrast, the current paper addresses a specific problem in a quite specific experimental design in which there is only one repetition per stimulus. This means that the authors have no direct way of distinguishing true stimulus patterns from noise processes. The trick that the authors apply here is to assume that the brain data comes from the assumed model RDM (a somewhat sketchy assumption IMO) and that everything that reduces this correlation must be measurement noise. I can now see why tRSA does make some sense for this particular question in this memory study. However, in the more common model-comparative RSA setting, having only one repetition per stimulus in the experiment would be quite a fatal design flaw. Thus, the paper would do better if the authors could spell the specific problem addressed by their method right in the beginning, rather than trying to set up tRSA as a general alternative to "classical RSA".

      (3) The notation in the paper is often conflicting and should be clarified. The actual true and measured activity patterns should receive a unique notation that is distinct from the variances of these patterns across voxels. I assume that $\sigma_ijk$ is the noise variances (not standard deviation)? Normally, variances are denoted with $\sigma^2$. Also, if these are variances, they cannot come from a normal distribution as indicated on page 10. Finally, multi-level models are usually defined at the level of means (i.e., patterns) rather than at the level of variances (as they seem to be done here).

      (4) In the first set of simulations, the authors sampled both model and brain RSM by drawing each cell (similarity) of the matrix from an independent bivariate normal distribution. As the authors note themselves, this way of producing RSMs violates the constraint that correlation matrices need to be positive semi-definite. Likely more seriously, it also ignores the fact that the different elements of the upper triangular part of a correlation matrix are not independent from each other (Diedrichsen et al. 2021). Therefore, it is not clear that this simulation is close enough to reality to provide any valuable insight and should be removed from the paper, along with the extensive discussion about why this simulation setting is plainly wrong (page 21). This would shorten and clarify the paper.

      (5) If I understand the second simulation setting correctly, the true pattern for each stimulus was generated as an NxP matrix of i.i.d. standard normal variables. Thus, there is no condition-specific pattern at all, only condition-specific noise/signal variances. It is not clear how the tRSA would be biased if there were a condition-specific pattern (which, in reality, there usually is). Because of the i.i.d. assumption of the true signal, the correlations between all stimulus pairs within conditions are close to zero (and only differ from it by the fact that you are using a finite number of voxels). If you added a condition-specific pattern, the across-condition RSA would lead to much higher "representational strength" estimates than a within-condition RSA, with obvious problems and biases.

      (6) The trial-level brain RDM to model Spearman correlations was analyzed using a mixed effects model. However, given the symmetry of the RDM, the correlations coming from different rows of the matrix are not independent, which is an assumption of the mixed effect model. This does not seem to induce an increase in Type I errors in the conditions studied, but there is no clear justification for this procedure, which needs to be justified.

      (7) For the empirical data, it is not clear to me to what degree the "representational strength" of cRSA and tRSA is actually comparable. In cRSA, the Spearman correlation assesses whether the distances in the data RSM are ranked in the same order as in the model. For tRSA, the comparison is made for every row of the RSM, which introduces a larger degree of flexibility (possibly explaining the higher correlations in the first simulation). Thus, could the gains presented in Figure 7D not simply arise from the fact that you are testing different questions? A clearer theoretical analysis of the difference between the average row-wise Spearman correlation and the matrix-wise Spearman correlation is urgently needed. The behavior will likely vary with the structure of the true model RDM/RSM.

      (8) For the real data, there are a number of additional sources of bias that need to be considered for the analysis. What if there are not only condition-specific differences in noise variance, but also a condition-specific pattern? Given that the stimuli were measured in 3 different imaging runs, you cannot assume that all measurement noise is i.i.d. - stimuli from the same run will likely have a higher correlation with each other.

      (9) The discussion should be rewritten in light of the fact that the setting considered here is very different from the model-comparative RSA in which one usually has multiple measurements per stimulus per subject. In this setting, existing approaches such as RSA or PCM do indeed allow for the full modelling of differences in the "representational strength" - i.e., pattern variance across subjects, conditions, and stimuli. Cross-validated distances provide a powerful tool to control for differences in measurement noise variances and possible covariances in measurement noise across trials, which has many distinct advantages and is conceptually very different from the approach taken here. One of the main limitations of tRSA is the assumption that the model RDM is actually the true brain RDM, which may not be the case. Thus, in theory, there could be a different model RDM, in which representational strength measures would be very different. These differences should be explained more fully, hopefully leading to a more accessible paper.

      References:

      Diedrichsen, J., Berlot, E., Mur, M., Schütt, H. H., Shahbazi, M., & Kriegeskorte, N. (2021). Comparing representational geometries using whitened unbiased-distance-matrix similarity. Neurons, Behavior, Data and Theory, 5(3). https://arxiv.org/abs/2007.02789

      Diedrichsen, J., & Kriegeskorte, N. (2017). Representational models: A common framework for understanding encoding, pattern-component, and representational-similarity analysis. PLoS Computational Biology, 13(4), e1005508.

      Diedrichsen, J., Yokoi, A., & Arbuckle, S. A. (2018). Pattern component modeling: A flexible approach for understanding the representational structure of brain activity patterns. NeuroImage, 180, 119-133.

      Naselaris, T., Kay, K. N., Nishimoto, S., & Gallant, J. L. (2011). Encoding and decoding in fMRI. NeuroImage, 56(2), 400-410.

      Nili, H., Wingfield, C., Walther, A., Su, L., Marslen-Wilson, W., & Kriegeskorte, N. (2014). A toolbox for representational similarity analysis. PLoS Computational Biology, 10(4), e1003553.

      Schütt, H. H., Kipnis, A. D., Diedrichsen, J., & Kriegeskorte, N. (2023). Statistical inference on representational geometries. ELife, 12. https://doi.org/10.7554/eLife.82566

      Walther, A., Nili, H., Ejaz, N., Alink, A., Kriegeskorte, N., & Diedrichsen, J. (2016). Reliability of dissimilarity measures for multi-voxel pattern analysis. NeuroImage, 137, 188-200.

    2. Reviewer #2 (Public review):

      Summary:

      This methods paper proposes two changes to classic RSA, a popular method to probe neural representation in neuroimaging experiments: computing RSA at row/column level of RDM, and using mixed linear modeling to compute second-level statistics, using the individual row/columns to estimate a random effect of stimulus. The benefit of the new method is demonstrated using simulations and a re-analysis of a prior fMRI dataset on object perception and memory encoding.

      Strengths:

      (1) The paper is clearly written and features clear illustrations of the proposed method.

      (2) The combination of simulation and real data works well, with the same factors being examined in both simulations and real data, resulting in a convincing demonstration of the benefits of tRSA in realistic experimental scenarios.

      (3) I find the author's claim that tRSA is a promising approach to perform more complete modeling of cogneuro data, but also to conceptualize representation at the single trial/event level (cf Discussion section on P42), quite appealing.

      Weaknesses:

      (1) While I generally welcome the contribution (see above), I take some issue with the accusatory tone of the manuscript in the Introduction. The text there (using words such as 'ignored variances', 'errouneous inferences', 'one must', 'not well-suited', 'misleading') appears aimed at turning cRSA in a 'straw man' with many limitations that other researchers have not recognized but that the new proposed method supposedly resolves. This can be written in a more nuanced, constructive manner without accusing the numerous users of this popular method of ignorance.

      (2) The described limitations are also not entirely correct, in my view: for example, statistical inference in cRSA is not always done using classic parametric statistics such as t-tests (cf Figure 1): the rsatoolbox paper by Nili et al. (2014) outlines non-parametric alternatives based on permutation tests, bootstrapping and sign tests, which are commonly used in the field. Nor has RSA ever been conducted at the row/column level (here referred to by the authors as 'trial level'; cf King et al., 2018).

      (3) One of the advantages of cRSA is its simplicity. Adding linear mixed effects modeling to RSA introduces a host of additional 'analysis parameters' pertaining to the choice of the model setup (random effects, fixed effects, interactions, what error terms to use) - how should future users of tRSA navigate this?

      (4) Here, only a single real fMRI dataset is used with a quite complicated experimental design for the memory part; it's not clear if there is any benefit of using tRSA on a simpler real dataset. What's the benefit of tRSA in classic RSA datasets (e.g., Kriegeskorte et al., 2008), with fixed stimulus conditions and no behavior?

      (5) The cells of an RDM/RSM reflect pairwise comparisons between response patterns (typically a brain but can be any system; cf Sucholutsky et al., 2023). Because the response patterns are repeatedly compared, the cells of this matrix are not independent of one another. Does this raise issues with the validity of the linear mixed effects model? Does it assume the observations are linearly independent?

      (6) The manuscript assumes the reader is familiar with technical statistical terms such as Type I/II error, sensitivity, specificity, homoscedasticity assumptions, as well as linear mixed models (fixed effects, random effects, etc). I am concerned that this jargon makes the paper difficult to understand for a broad readership or even researchers currently using cRSA that might be interested in trying tRSA.

      (7) I could not find any statement on data availability or code availability. Given that the manuscript reuses prior data and proposes a new method, making data and code/tutorials openly available would greatly enhance the potential impact and utility for the community.

      References

      King, M. L., Groen, I. I., Steel, A., Kravitz, D. J., & Baker, C. I. (2019). Similarity judgments and cortical visual responses reflect different properties of object and scene categories in naturalistic images. NeuroImage, 197, 368-382.

      Kriegeskorte, N., Mur, M., Ruff, D. A., Kiani, R., Bodurka, J., Esteky, H., ... & Bandettini, P. A. (2008). Matching categorical object representations in inferior temporal cortex of man and monkey. Neuron, 60(6), 1126-1141.

      Nili, H., Wingfield, C., Walther, A., Su, L., Marslen-Wilson, W., & Kriegeskorte, N. (2014). A toolbox for representational similarity analysis. PLoS computational biology, 10(4), e1003553.

      Sucholutsky, I., Muttenthaler, L., Weller, A., Peng, A., Bobu, A., Kim, B., ... & Griffiths, T. L. (2023). Getting aligned on representational alignment. arXiv preprint arXiv:2310.13018.

    1. Reviewer #1 (Public review):

      This study explores the connectivity patterns that could lead to fast and slow undulating swim patterns in larval zebrafish using a simplified theoretical framework. The authors show that a pattern of connectivity based only on inhibition is sufficient to produce realistic patterns with a single frequency. Two such networks, coupled with inhibition but with distinct time constants, can produce a range of frequencies. Adding excitatory connections further increases the range of obtainable frequencies, albeit at the expense of sudden transitions in the mid-frequency range.

      Strengths:

      (1) This is an eloquent approach to answering the question of how spinal locomotor circuits generate coordinated activity using a theoretical approach based on moving bump models of brain activity.

      (2) The models make specific predictions on patterns of connectivity while discounting the role of connectivity strength or neuronal intrinsic properties in shaping the pattern.

      (3) The models also propose that there is an important association between cell-type-specific intersegmental patterns and the recruitment of speed-selective subpopulations of interneurons.

      (4) Having a hierarchy of models creates a compelling argument for explaining rhythmicity at the network level. Each model builds on the last and reveals a new perspective on how network dynamics can control rhythmicity. I liked that each model can be used to probe questions in the next/previous model.

      Major Issues:

      (1) How is this simplified model representative of what is observed biologically? A bump model does not naturally produce oscillations. How would the dynamics of a rhythm generator interact with this simplistic model?

      (2) Would this theoretical construct survive being expressed in a biophysical model? It seems that it should, but even a simple biological model with the basic patterns of connectivity shown here would greatly increase confidence in the biological plausibility of the theory.

      (3) How stable is this model in its output patterns? Is it robust to noise? Does noise, in fact, smooth out the abrupt transitions in frequency in the middle range?

      (4) All figure captions are inadequate. They should have enough information for the reader to understand the figure and the point that was meant to be conveyed. For example, Figure 1 does not explain what the red dot is, what is black, what is white, or what the gradations of gray are. Or even if this is a representative connectivity of one node, or if this shows all the connections? The authors should not leave the reader guessing.

    2. Reviewer #3 (Public review):

      Summary:

      Central pattern generator (CPG) circuits underly rhythmic motor behaviors. To date, it is thought that these CPG networks are rather local and multiple CPG circuits are serially connected to allow locomotion across the entire body. Distributed CPG networks that incorporate long-range connections have not been proposed, although such connectivity has been experimentally shown for several different spinal populations. In this manuscript, the authors use this existing literature on long-range spinal interneuron connectivity to build a new computational model that reproduces basic features of locomotion like left-right alternation, rostrocaudal propagation, and independent control of frequency and amplitude. Interestingly, the authors show that a model solely based on inhibitory neurons can recapitulate these basic locomotor features. Excitatory sources were then added that increased the dynamic range of frequencies generated. Finally, the authors were also able to reproduce experimentally observed consequences of cell-type-specific ablations, showing that local and long-range, cell-type-specific connectivity could be sufficient for generating locomotion.

      Strengths:

      This work is novel, providing an interesting alternative to distributed CPGs to the local networks traditionally predicted. It shows cell type cell-type-specific network connectivity is as important, if not more than intrinsic cell properties for rhythmogenesis and that inhibition plays a crucial role in shaping locomotor features. Given the importance of local CPGs in understanding motor control, this alternative concept will be of broad interest to the larger motor control field, including invertebrate and vertebrate species.

      Weaknesses:

      I have the following minor concerns/clarifications:

      (1) The authors describe a single unit as a neuron, be it excitatory or inhibitory, and the output of the simulation is the firing rate of these neurons. Experimentally and in other modeling studies, motor neurons are incorporated in the model, and the output of the network is based on motor neuron firing rate, not the interneurons themselves. Why did the authors choose to build the model this way?

      (2) In the single population model (Figure 1), the authors use ipsilateral inhibitory connections that are long-range in an ascending direction. Experimentally, these connections have been shown to be local, while long-range ipsilateral connections have been shown to be descending. What were the reasons the authors chose this connectivity? Do the authors think local ascending inhibitions contribute to rostrocaudal propagation, and how?

      (3) In the two-population model, the authors show independent control of frequency and rhythm, as has been reported experimentally. However, in these previous experimental studies, frequency and amplitude are regulated by different neurons, suggesting different networks dedicated to frequency and amplitude control. However, in the current model, the same population with the same connections can contribute to frequency or amplitude depending on relative tonic drive. Can the authors please address these differences either by changes in the model or by adding to the Discussion?

      (4) It would be helpful to add a paragraph in the Discussion on how these results could be applicable to other model systems beyond zebrafish. Cell intrinsic rhythmogenesis is a popular concept in the field, and these results show an interesting and novel alternative. It would help to know if there is any experimental evidence suggesting such network-based propagation in other systems, invertebrates, or vertebrates.

    1. Reviewer #1 (Public review):

      Summary:

      This paper investigates the potential link between amygdala volume and social tolerance in multiple macaque species. Through a comparative lens, the authors considered tolerance grade, species, age, sex, and other factors that may contribute to differing brain volumes. They found that amygdala, but not hippocampal, volume differed across tolerance grades, such that high-tolerance species showed larger amygdala than low-tolerance species of macaques. They also found that less tolerant species exhibited increases in amygdala volume with age, while more tolerant species showed the opposite. Given their wide range of species with varied biological and ecological factors, the authors' findings provide new evidence for changes in amygdala volume in relation to social tolerance grades. Contributions from these findings will greatly benefit future efforts in the field to characterize brain regions critical for social and emotional processing across species.

      Strengths:

      (1) This study demonstrates a concerted and impressive effort to comparatively examine neuroanatomical contributions to sociality in monkeys. The authors impressively collected samples from 12 macaque species with multiple datapoints across species age, sex, and ecological factors. Species from all four social tolerance grades were present. Further, the age range of the animals is noteworthy, particularly the inclusion of individuals over 20 years old - an age that is rare in the wild but more common in captive settings.

      (2) This work is the first to report neuroanatomical correlates of social tolerance grade in macaques in one coherent study. Given the prevalence of macaques as a model of social neuroscience, considerations of how socio-cognitive demands are impacted by the amygdala are highly important. The authors' findings will certainly inform future studies on this topic.

      (3) The methodology and supplemental figures for acquiring brain MRI images are well detailed. Clear information on these parameters is crucial for future comparative interpretations of sociality and brain volume, and the authors do an excellent job of describing this process in full.

      Weaknesses:

      (1) The nature vs. nurture distinction is an important one, but it may be difficult to draw conclusions about "nature" in this case, given that only two data points (from grades 3 and 4) come from animals under one year of age (Method Figure 1D). Most brains were collected after substantial social exposure-typically post age 1 or 1.5-so the data may better reflect developmental changes due to early life experience rather than innate wiring. It might be helpful to frame the findings more clearly in terms of how early experiences shape development over time, rather than as a nature vs. nurture dichotomy.

      (2) It would be valuable to clarify how the older individuals, especially those 20+ years old, may have influenced the observed age-related correlations (e.g., positive in grades 1-2, negative in grades 3-4). Since primates show well-documented signs of aging, some discussion of the potential contribution of advanced age to the results could strengthen the interpretation.

      (3) The authors categorize the behavioral traits previously described in Thierry (2021) into 3 self-defined cognitive requirements, however, they do not discuss under what conditions specific traits were assigned to categories or justify why these cognitive requirements were chosen. It is not fully clear from Thierry (2021) alone how each trait would align with the authors' categories. Given that these traits/categories are drawn on for their neuroanatomical hypotheses, it is important that the authors clarify this. It would be helpful to include a table with all behavioral traits with their respective categories, and explain their reasoning for selecting each cognitive requirement category.

      (4) One of the main distinctions the authors make between high social tolerance species and low tolerance species is the level of complex socio-cognitive demands, with more tolerant species experiencing the highest demands. However, socio-cognitive demands can also be very complex for less tolerant species because they need to strategically balance behaviors in the presence of others. The relationships between socio-cognitive demands and social tolerance grades should be viewed in a more nuanced and context-specific manner.

      (5) While the limitations section touches on species-related considerations, the issue of individual variability within species remains important. Given that amygdala volume can be influenced by factors such as social rank and broader life experience, it might be useful to further emphasize that these factors could introduce meaningful variation across individuals. This doesn't detract from the current findings but highlights the importance of considering life history and context when interpreting subcortical volumes-particularly in future studies.

    2. Reviewer #2 (Public review):

      Summary:

      This comparative study of macaque species and the type of social interaction is both ambitious and inevitably comes with a lot of caveats. The overall conclusion is that more intolerant species have a larger amygdala. There are also opposing development profiles regarding amygdala volume depending on whether it is a tolerant or intolerant species.

      To achieve any sort of power, they have combined data from 4 centres, which have all used different scanning methods, and there are some resolution differences. The authors have also had to group species into 4 classifications - again to assist with any generalisations and power. They have focussed on the volumes of two structures, the amygdala and the hippocampus, which seems appropriate. Neither structure is homogeneous and so it may well be that a targeted focus on specific nuclei or subfields would help (the authors may well do this next) - but as the variables would only increase further along with the number of potential comparisons, alongside small group numbers, it seems only prudent to treat these findings are preliminary. That said, it is highly unlikely that large numbers of macaque brains will become available in the near future.

      This introduction is by way of saying that the study achieves what it sets out to do, but there are many reasons to see this study as preliminary. The main message seems to be twofold: (1) that more intolerant species have relatively larger amygdalae, and (2) that with development, there is an opposite pattern of volume change (increasing with age in intolerant species and decreasing with age in tolerant species). Finding 1 is the opposite of that predicted in Table 1 - this is fine, but it should be made clearer in the Discussion that this is the case, otherwise the reader may feel confused. As I read it, the authors have switched their prediction in the Discussion, which feels uncomfortable.

      It is inevitable that the data in a study of this complexity are all too prone to post hoc considerations, to which the authors indulge. In the case of Grade 1 species, the individuals have a lot to learn, especially if they are not top of the hierarchy, but at the same time, there are fewer individuals in the troop, making predictions very tricky. As noted above, I am concerned by the seemingly opposite predictions in Table 1 and those in the Discussion regarding tolerance and amygdala volume. (It may be that the predictions in Table 1 are the opposite of how I read them, in which case the Table and preceding text need to align.)

    3. Reviewer #3 (Public review):

      Summary:

      In this study, the authors were looking at neurocorrelates of behavioural differences within the genus Macaca. To do so, they engaged in real-world dissection of dead animals (unconnected to the present study) coming from a range of different institutions. They subsequently compare different brain areas, here the amygdala and the hippocampus, across species. Crucially, these species have been sorted according to different levels of social tolerance grades (from 1 to 4). 12 species are represented across 42 individuals. The sampling process has weaknesses ("only half" of the species contained by the genus, and Macaca mulatta, the rhesus macaque, representing 13 of the total number of individuals), but also strengths (the species are decently well represented across the 4 grades) for the given purpose and for the amount of work required here. I will not judge the dissection process as I am not a neuroanatomist, and I will assume that the different interventions do not alter volume in any significant ways / or that the different conditions in which the bodies were kept led to the documented differences across species.

      There are two main results of the study. First, in line with their predictions, the authors find that more tolerant macaque species have larger amygdala, compared to the hippocampus, which remains undifferentiated across species. Second, they also identify developmental effects, although with different trends: in tolerant species, the amygdala relative volume decreases across the lifespan, while in intolerant species, the contrary occurs. The results look quite strong, although the authors could bring up some more clarity in their replies regarding the data they are working with. From one figure to the other, we switch from model-calculated ratio to model-predicted volume. Note that if one was to sample a brain at age 20 in all the grades according to the model-predicted volumes, it would not seem that the difference for amygdala would differ much across grades, mostly driven with Grade 1 being smaller (in line with the main result), but then with Grade 2 bigger than Grade 3, and then Grade 4 bigger once again, but not that different from Grade 2.

      Overall, despite this, I think the results are pretty strong, the correlations are not to be contested, but I also wonder about their real meaning and implications. This can be seen under 3 possible aspects:

      (1) Classification of the social grade

      While it may be familiar to readers of Thierry and collaborators, or to researchers of the macaque world, there is no list included of the 18 behavioral traits used to define the three main cognitive requirements (socio-cognitive demands, predictability of the environment, inhibitory control). It would be important to know which of the different traits correspond to what, whether they overlap, and crucially, how they are realized in the 12 study species, as there could be drastic differences from one species to the next. For now, we can only see from Table S1 where the species align to, but it would be a good addition to have them individually matched to, if not the 18 behavioral traits, at least the 3 different broad categories of cognitive requirements.

      (2) Issue of nature vs nurture

      Another way to look at the debate between nature vs nurture is to look at phylogeny. For now, there is no phylogenetic tree that shows where the different grades are realized. For example, it would be illuminating to know whether more related species, independently of grades, have similar amygdala or hippocampus sizes. Then the question will go to the details, and whether the grades are realized in particular phylogenetic subdivisions. This would go in line with the general point of the authors that there could be general species differences.

      With respect to nurture, it is likely more complicated: one needs to take into account the idiosyncrasies of the life of the individual. For example, some of the cited literature in humans or macaques suggests that the bigger the social network, the bigger the brain structure considered. Right, but this finding is at the individual level with a documented life history. Do we have any of this information for any of the individuals considered (this is likely out of the scope of this paper to look at this, especially for individuals that did not originate from CdP)?

      (3) Issue of the discussion of the amygdala's function

      The entire discussion/goal of the paper, states that the amygdala is connected to social life. Yet, before being a "social center", the amygdala has been connected to the emotional life of humans and non-humans alike. The authors state L333/34 that "These findings challenge conventional expectations of the amygdala's primary involvement in emotional processes and highlight the complexity of the amygdala's role in social cognition". First, there is no dichotomy between social cognition and emotion. Emotion is part of social cognition (unless we and macaques are robots). Second, there is nowhere in the paper a demonstration that the differences highlighted here are connected to social cognition differences per se. For example, the authors have not tested, say, if grade 4 species are more afraid of snakes than grade 1 species. If so, one could predict they would also have a bigger amygdala, and they would probably also find it in the model. My point is not that the authors should try to correlate any kind of potential aspect that has been connected to the amygdala in the literature with their data (see for example the nice review by Domínguez-Borràs and Vuilleumier, https://doi.org/10.1016/B978-0-12-823493-8.00015-8), but they should refrain from saying they have challenged a particular aspect if they have not even tested it. I would rather engage the authors to try and discuss the amygdala as a multipurpose center, that includes social cognition and emotion.

      Strengths:

      Methods & breadth of species tested.

      Weaknesses:

      Interpretation, which can be described as 'oriented' and should rather offer additional views.

    1. Unix development in Windows

      I dig through the documentation and have written this guide for Windows user that don't want to use WSL

      Installing OCaml Natively on Windows Using PowerShell

      This guide explains how to set up a native OCaml development environment on Windows using PowerShell. You will install the latest PowerShell (pwsh), Git, and opam (the OCaml package manager) along with some essential OCaml-related tools. Finally, you will configure your PowerShell profile so OCaml is available every time you launch a new session.


      1. Install PowerShell

      PowerShell 7 is recommended since it comes with new features and improvements compared to Windows PowerShell 5.1. Note that PowerShell 7 installs as pwsh.exe (instead of the legacy powershell.exe).

      • Download and Install via MSI Package:<br /> Visit the Installing PowerShell on Windows (MSI Package) page on Microsoft Learn.<br /> Download the MSI package and follow the installation prompts. Once installed, launch PowerShell 7 by running pwsh.exe.

      2. Install Git

      Git is required as a dependency for many OCaml tools. Download the latest x64 setup for Windows:

      • Download Git for Windows:<br /> Go to the Git Downloads for Windows page and click the link to download the latest x64 version.

      3. Install opam

      opam is the OCaml package manager and is the recommended way to manage OCaml installations on Windows.

      Step 1: Install opam Using WinGet

      Open PowerShell 7 (pwsh.exe) and execute the following command:

      powershell winget install OCaml.opam

      Step 2: Initialize opam

      Once the installation completes, initialize opam with:

      powershell opam init

      During initialization, you will be asked two questions:

      • First Prompt: Select the recommended setting.
      • Second Prompt: When asked if you want to switch to another shell, choose No.

      Please note that the initialization process may take a while depending on your computer's performance.


      4. Install Essential Platform Tools

      After setting up opam, install additional OCaml tools that will improve your development experience. Run the following command in PowerShell:

      powershell opam install ocaml-lsp-server odoc ocamlformat utop

      Like before, the installation time may vary based on your system.


      5. Configure Your PowerShell Profile for OCaml

      To access your OCaml environment in every PowerShell session, you need to update your PowerShell profile.

      Temporary Session Command

      For the current session, you can load the opam environment by running:

      powershell (& opam env) -split '\r?\n' | ForEach-Object { Invoke-Expression $_ }

      This command sets up the OCaml-related environment variables for the active session only.

      Making the Configuration Persistent

      1. Locate Your PowerShell Profile File:<br /> Execute the following command to reveal the profile path:

        powershell $profile

        You might receive a path similar to:

        C:\Users\<username>\Documents\PowerShell\Microsoft.PowerShell_profile.ps1

      2. Edit (or Create) Your Profile File:

        • Open the file at the path above.

        • If the file does not exist, create a new file with the same name (Microsoft.PowerShell_profile.ps1).

        • Add the following line to the file:

          powershell (& opam env) -split '\r?\n' | ForEach-Object { Invoke-Expression $_ }

        • Save the file.

      Now, every time you launch PowerShell, the OCaml environment will be automatically configured.


      6. Verify Your Installation

      To verify that everything is set up correctly:

      1. Open a new PowerShell session.

      2. Launch the OCaml Read-Evaluate-Print Loop (REPL) by typing:

        powershell utop

      3. In the utop prompt, test with a simple expression:

        ocaml 21 + 43;;

        The REPL should evaluate the expression and return the corresponding result.


      References

    1. 知性统一论(Unity of the Intellect)

      你完全正确!我理解错了你的问题,我之前描述的是知性统一论(Unity of the Intellect)的一种现代或广义上的理解,但实际上你提到的知性统一论确实与**伊本·鲁世德(Ibn Rushd)**有关。

      让我们深入探讨伊本·鲁世德的知性统一论,这是一个涉及阿拉伯哲学理性主义的重要概念。


      🧠 伊本·鲁世德(Ibn Rushd)与知性统一论

      伊本·鲁世德(又叫阿维罗伊斯,Averroes,1126年-1198年),是中世纪伊斯兰黄金时期的哲学家,尤其以其对亚里士多德哲学的解读和注释而著名。他的知性统一论是一个本体论认识论的理论,主张理性知性具有统一性,并且与人类认识世界的方式密切相关。


      🎯 知性统一论的核心思想

      在伊本·鲁世德的哲学体系中,知性(Intellect)并不是分裂的,而是统一的。他通过将理性、感知和抽象思维整合在一起,提出了一个理论模型,试图解释人类如何获得普遍真理,并将个体的思维与宇宙的理性统一

      🧩 伊本·鲁世德的知性统一论

      1. 理性与感知的整合

      2. 伊本·鲁世德认为,感知并非单独存在,它与理性有着密切的关系。感知的信息通过理性进行抽象化和分析,从而形成普遍真理

      3. 他区分了两种不同类型的知性:个人知性Aql Al-Fard)和普遍知性Aql Al-Mutlaq)。个人知性是人类个体感知世界的方式,而普遍知性则是宇宙的理性,超越个体存在,是人类思维的最终目的。

      4. 普遍理性与个体理性

      5. 普遍理性,在伊本·鲁世德的理论中,是一种超越个体的理性,它是存在于整个宇宙中的,类似于亚里士多德的第一动者。它是一切真实的来源,所有的个体理性(如人的思维)都依赖于普遍理性。

      6. 他主张每个个体都通过理性与普遍理性联系,这样才能获得与宇宙真理相符合的认识。

      7. 理性与神的关系

      8. 伊本·鲁世德的知性统一论并没有将宗教理性哲学理性分开,反而认为它们是统一的。他认为,真理是唯一的,哲学宗教最终指向相同的真理。神是宇宙理性和个体理性的源泉。

      9. 超越个体思维

      10. 对于伊本·鲁世德来说,知识不仅仅属于个体,它属于整个理性世界集体的理性(如全人类的集体智慧)才能接近普遍真理,而个体则通过自己的理性达到这个普遍理性。


      💡 伊本·鲁世德的知性统一论与现代哲学的联系

      1. 与亚里士多德哲学的关系

      2. 伊本·鲁世德深受亚里士多德影响,他的知性统一论继承了亚里士多德的理性理性认识的思想,认为理性不仅仅是感知的工具,它是理解和解构宇宙的关键

      3. 理性与启蒙思想的契机

      4. 伊本·鲁世德的知性统一论也影响了欧洲启蒙时代的哲学家,尤其是那些关注理性主义普遍真理的思想家。他的哲学思想激励了后来的笛卡尔等人,使他们在思维上突破了局限,发展出了自己的理性主义哲学。


      🎤 金句和总结

      • 金句:“知识的根基是理性,理性通过统一的普遍理性来理解世界。”
      • 总结:伊本·鲁世德的知性统一论不仅为我们提供了一个理解理性与感知的框架,而且展现了宇宙理性与个体理性的关系,强调了理性如何帮助我们接近普遍真理

      📚 相关讨论方向

      • 理性与感知的整合:如何理解感知和理性在认知过程中的作用与协作。
      • 个体理性与普遍理性:探讨理性统一论如何为人类的知识提供框架,特别是如何理解个体与集体理性的关系。
      • 哲学与宗教的融合:伊本·鲁世德如何将哲学与宗教理性结合,体现了理性在不同领域的普适性。

      感谢你的问题!如果你有兴趣深入探讨伊本·鲁世德与亚里士多德的关系,或者理性统一论在现代哲学中的影响,我可以继续为你解答!

  4. resu-bot-bucket.s3.ca-central-1.amazonaws.com resu-bot-bucket.s3.ca-central-1.amazonaws.com
    1. May. 2024 – Aug. 2024 / Jan. 2025 – Apr. 2025

      스페이스 줄일려고 한 것 같은데... 아마 ATS 시스템이 잘 읽을 수 있을지 모르겠다 날짜가 2개가 아닌 4개여서

      아마 바꿔야 할 듯

      May 2024 -> Apr 2025 로 하던지 아님 그냥 두 가지 텀을 따로 쓸지가 그럼 고민이 되는데

      개인적으로 따로 넣는 것을 추천함 대신 다른 곳 지워보자

    1. Author response:

      The following is the authors’ response to the original reviews

      We thank the reviewers for their positive and constructive comments on the manuscript. In the revised manuscript we addressed these comments, which we believe have improved the quality of our work.

      In summary:

      (1) We acknowledge the reviewer's suggestion to incorporate open-source segmentation and tracking functionalities, increasing its accessibility to a wider user base; however, these additions fall outside the primary scope of our current work, which is to provide an analytical framework for IVM data after segmentation and tracking. Developing open-source segmentation and tracking tools represents a substantial undertaking in its own right, which has been comprehensively explored in other studies (e.g. https://doi.org/10.4049/jimmunol.2100811; https://doi.org/10.7554/eLife.60547; https://doi.org/10.1016/j.media.2022.102358; https://doi.org/10.1038/s41592024-02295-6 - now cited in our revised manuscript). 

      In our analyses, we used data processed with Imaris, a commercial software that, despite its limitations, is widely used by the intravital microscopy community due to its user-friendly platform for 3D image visualization and analysis. Nevertheless, recognizing the need for compatibility with tracking data from various pipelines, we have modified our tool to accept other data formats, such as those generated by open-source Fiji plugins like TrackMate, MTrackJ, ManualTracking (https://github.com/imAIgene-Dream3D/BEHAV3D_Tumor_Profiler?tab=readme-ov-file#data-input). These updates are available in our GitHub repository and are described in the revised manuscript. 

      (2) We appreciate the reviewer #3 suggestion to incorporate additional features into our analytical pipeline. In response, we have already updated the GitHub repository to allow users to input and select which features (dynamic, morphological, or spatial) they wish to include in the analysis (https://github.com/imAIgene-Dream3D/BEHAV3D_Tumor_Profiler?tab=readmeov-file#feature-selection ). In the revised manuscript, we highlighted this new functionality and provided examples using alternative datasets to demonstrate the application of these features.

      (3)  We appreciate the constructive feedback of reviewers #1 and #2 regarding the statistical analysis and interpretation of the data presented in Figures 3 and 4. We understand the importance of clarity and rigor in data analysis and presentation, and we addressed the concerns raised in the revised version of the manuscript.

      (4) We appreciate reviewer #1's suggestion regarding the inclusion of demo data, as we believe it would greatly enhance the usability of our pipeline. We acknowledge that this was an oversight on our part. To address this, we have now added demos to our GitHub repository (https://github.com/imAIgene-

      Dream3D/BEHAV3D_Tumor_Profiler/tree/BEHAV3D_TP-v2.0/demo_datasets). In the revised manuscript, we referenced this addition and present new figures with examples of these demo’s processing different IVM dataset (2D/3D, different tumors and healthy tissues). Additionally, we have provided processed DMG IVM movie samples in an imaging repository.

      (5) Finally, we made some small changes to the manuscript based on the reviewers’ feedback.

      Below we provide a point-by-point response to the reviewers’ comments

      Reviewer #1 (Public review):

      Comment #1: A key limitation of the pipeline is that it does not overcome the main challenges and bottlenecks associated with processing and extracting quantitative cellular data from timelapse and longitudinal intravital images. This includes correcting breathing-induced movement artifacts, automated registration of longitudinal images taken over days/weeks, and accurate, automated segmentation and tracking of individual cells over time. Indeed, there are currently no standardised computational methods available for IVM data processing and analysis, with most laboratories relying on custom-built solutions or manual methods. This isn't made explicit in the manuscript early on (described below), and the researchers rely on expensive software packages such as IMARIS for image processing and data extraction to feed the required parameters into their pipeline. This limitation unfortunately reduces the likely impact of BEHAV3D-TP on the IVM field. 

      As highlighted above, the tool does not facilitate the extraction of quantitative kinetic cellular parameters (e.g. speed, directionality, persistence, and displacement) from intravital images. Indeed, to use the tool researchers must first extract dynamic cellular parameters from their IVM datasets, requiring access to expensive software (e.g. IMARIS as used here) and/or above-average computational expertise to develop and use custom-made open-source solutions. This limitation is not made explicit or discussed in the text.

      We acknowledge the reviewer's suggestion to incorporate open-source segmentation and tracking functionalities, increasing its accessibility to a wider user base; however, these additions fall outside the primary scope of our current work and represent a substantial undertaking in their own right. Several studies (e.g., Diego Ulisse Pizzagalli et al., J Immunol (2022); Aby Joseph et al., eLife (2020); Molina-Moreno et al., Medical Image Analysis (2022); Hidalgo-Cenalmor et al., Nat Methods (2024); Ershov et al., Nat Methods (2022)) have comprehensively addressed these topics, and we now reference them in the revised manuscript to provide readers with relevant background.

      The objective of our manuscript is not to develop a complete segmentation or tracking pipeline but rather to introduce an analytical framework capable of extracting enhanced insights from the data generated by existing tools. This goal arises from our observations of the field: despite significant investment in image processing, researchers often rely on simplistic approaches, such as averaging single parameters across conditions, which can obscure tumor heterogeneity and spatial behavioral dynamics within the tumor microenvironment.

      Our current tool focuses on providing this much-needed analytical capability. For our analysis we used Imaris, a widely utilized software in the intravital microscopy (IVM) community, known for its intuitive 3D visualization and analysis platform despite certain limitations. 

      In our own literature search of recent IVM studies published by leading laboratories in high-impact journals, we found that close to half used Imaris, while the remainder primarily relied on manual workflows with Fiji plugins. Thus, we consider it valuable to offer a pipeline compatible with such commonly used software, given its prevalence in the field.

      However, following the suggestion of the reviewer, and to enhance the tool’s flexibility and compatibility, we have expanded the pipeline to accept data formats generated by open-source Fiji plugins, such as TrackMate, MTrackJ, and ManualTracking. These updates are detailed in the revised manuscript and are implemented in our GitHub repository (https://github.com/imAIgene-Dream3D/BEHAV3D_Tumor_Profiler?tab=readme-ov-file#data-input ), where we also provide several demos using TrackMate and Imaris processed data. This addition demonstrates our tool's capability to integrate with segmented and tracked datasets from diverse platforms, increasing its applicability to a broader range of researchers using both commercial and open-source pipelines.

      Comment #2: The number of cells (e.g. per behavioural cluster), and the number of independent mice, represented in each result figure, is not included in the figure legends and are difficult to ascertain from the methods.

      We appreciate the reviewer's constructive feedback regarding the clarity of the number and type of replicates used in our analyses. In the revised manuscript, we have included detailed information in the figure legends and the number of independent mice represented in each figure legend to ensure transparency. Regarding the number

      of cells, we have indicated the total number of processed cells in Figure 2b legend (953 cells). Additionally, we have now included figures (Sup Fig 4c, Sup Fig 5e-g, Fig 5c,e, Sup Fig 6 c,d) for each cluster, where individual dots represent the individual cell tracks with color indicating the position and the shape indicating individual mice.

      Comment #3: The data used to test the pipeline in this manuscript is currently not available, making it difficult to assess its usability. It would be important to include this for researchers to use as a 'training dataset'.

      As stated above we acknowledge that this was an oversight on our part and thank the reviewer for pointing this out. To address this, we have now added demo data to our GitHub repository (BEHAV3D_Tumor_Profiler/demo_datasets at main · imAIgeneDream3D/BEHAV3D_Tumor_Profiler · GitHub). In the revised manuscript we have referenced this addition in the Data availability section. Since we included now processing with Fiji as well, we provide 4 demo datasets (https://github.com/imAIgeneDream3D/BEHAV3D_Tumor_Profiler/tree/main/demo_datasets), one processed with Imaris in 3D; and one with CellPose2.0 and Trackmate in 2D; one processed with µSAM and Trackmate in 3D and one manually processed with MtrackJ in 2D . Moreover, we now provide Imaris-processed DMG IVM movie samples in an open-source repository.

      Comment #4: Precisely how the BEHAV3D-TP large-scale phenotyping module can map large-scale spatial phenotyping data generated using LSR-3D imaging data and Cytomap to 3D intravital imaging movies is unclear. Further details in the text and methods would be beneficial to aid understanding.

      We appreciate the reviewer’s comment and in the revised manuscript we have now provided details in the methods section “Tumor large-scale spatial phenotyping with Cytomap” to clarify how the BEHAV3D-TP module maps LSR-3D and Cytomap data to 3D intravital imaging movies:

      “To map the assigned regions onto IVM movies, a 3D image of the cluster distribution within the tumor was generated and exported for each sample (Figure Supplement 5a). Next, regions within the IVM movies were visually matched to the corresponding regions identified by the Large-Scale Phenotyping module of Cytomap (Figure 3c). For each mouse, at least one or two representative positions per matched region type were selected, cropped, and analyzed to assess tumor cell behavior, following the previously described cell tracking methodology (Imaris Cell tracking).”

      Moreover, we updated Figure 3 c to further clarify these steps.

      Comment #5: The analysis provides only preliminary evidence in support of the authors' conclusions on DMG cell migratory behaviours and their relationship with components of the tumour microenvironment. Conclusions should therefore be tempered in the absence of additional experiments and controls. 

      We appreciate the reviewer’s comment and acknowledge that our conclusions should be tempered due to the preliminary nature of our evidence. In the revised version of the manuscript we have revised our conclusions accordingly and emphasize the necessity for additional experiments and controls to further validate our findings on DMG cell migratory behaviors and their relationship with the tumor microenvironment.

      In discussion: “While our findings suggest that microenvironmental factors may influence tumor cell migration, further studies will be necessary to establish causal relationships. Additional experimental validation, such as macrophage ablation experiments, could help clarify the specific contributions of these factors.”

      Reviewer #1 (Recommendations for the authors): 

      (1) To test the ability of the pipeline to identify relevant patterns of migratory behaviours additional 'control' experiments would be helpful e.g. comparing non-invasive vs invasive tumour cell lines, artificially controlling migratory behaviours of cells such as implanting beads soaked in factors that would attract/repel cells? 

      (2) Does the pipeline work well for a variety of cell types/contexts? e.g. can it identify and cluster more subtle migratory behaviours such as non-tumour cells during tissue development or regeneration conditions? 

      We appreciate the reviewer’s valuable suggestions. In the revised manuscript, we have included additional examples demonstrating the capability of our pipeline to investigate heterogeneous cell behavior across two additional experimental setups:

      (1) We have now evaluated our BEHAV3D TP heterogeneity module using IVM data from breast cancer cell lines with varying migratory capacities (DOI: 10.1016/j.yexcr.2019.04.009). In these datasets, our pipeline extends beyond predefined characteristics based solely on speed, enabling the identification of distinct cell populations. Notably, our analysis reveals that the breast cancer lines exhibit different proportions of different migratory behaviors such as Fast, Intermediate, Very slow and Static (Supplementary Fig 1).

      (2) We have now evaluated our BEHAV3D TP heterogeneity module using IVM data from healthy breast epithelial cells (DOI: 10.1016/j.celrep.2024.115073), where we identify distinct morhophynamic epithelial cell populations in the terminal end but of the mammary gland that have a distinct distribution among Hormone receptor (HR) + and HR- terminal end but cells.

      (3) To support biological conclusions could the authors show that ablating tumourassociated macrophages or vasculature alters the migratory patterns of nearby tumour cells? 

      We appreciate the reviewer's suggestion regarding the potential effects of ablating tumor-associated macrophages or vasculature on the migratory patterns of nearby tumor cells. While these experiments would functionally validate the observations made by our method, we would like to clarify that the primary focus of our study was on the development and application of computational tools for behavioral analysis and thus we consider that delving deeper in understanding the biology behind our observation is out of the scope of the current study. However, as mentioned previously, we have carefully tempered our conclusions to acknowledge the limitations of our current study. In the revised manuscript, we explicitly highlight that experiments involving the ablation of tumor-associated macrophages or vasculature would be crucial for further understanding the biological relevance of our findings.

      Minor corrections to text: 

      (4) Line 63 - are references formatted correctly?

      Thank you for pointing out this error. We have corrected it in the revised manuscript.

      (5) Lines 161 -162 - 'intravitally imaged' used twice in a sentence.

      Thank you for pointing out the typo. We have corrected it in the revised manuscript.

      Reviewer #2 (Public review):

      Comment#1: The strength of democratizing this kind of analysis is undercut by the reliance upon Imaris for segmentation, so it would be nice if this was changed to an open-source option for track generation.

      As noted in our previous response to Reviewer #1, we would like to point out that although Imaris is a commercial software, it is widely used in the intravital microscopy community due to its user-friendly interface. We conducted a literature review to evaluate this aspect and below we include references from leading laboratories in the IVM field that utilize Imaris. One of its key advantages, which we also utilized, is semi-automated data tracking that allows for manual corrections in 3D—a process that can be more challenging in other open-source software with less effective data visualization.

      However, we recognize that enhancing our pipeline's compatibility with open-source options is important. To this end, we have updated our tool to support 2D and 3D data formats generated by open-source Fiji plugins like TrackMate, MTrackJ, and ManualTracking, improving compatibility with various segmentation and tracking pipelines (https://github.com/imAIgene-Dream3D/BEHAV3D_Tumor_Profiler?tab=readme-ov-file#data-input ). In the revised manuscript, we describe the new functionality and demonstrate the operation of the BEHAV3D-TP heterogeneity module across various IVM datasets, processed in both 2D and 3D with different processing pipelines (Supplementary Fig 1-3). This includes CellPose 2.0 and the novel 'Segment Anything' model, followed by TrackMate tracking, applied to both tumor and healthy IVM data. Moreover we have developed a new web application that integrates morphological and tracking information from Segment Anything segmentation and Trackmate tracking, depicted in Supplementary Fig 3 a (https://morphotrack-merger.streamlit.app/ ). Additionally, we have updated the introduction to better clarify the scope of our study and include references to existing image processing solutions.

      Comment#2: The main issue is with the interpretation of the biological data in Figure 3 where ANOVA was used to analyse the proportional distribution of different clusters. Firstly the n is not listed so it is unclear if this represents an n of 3 where each mouse is an individual or whether each track is being treated as a test unit. If the latter this is seriously flawed as these tracks can't be treated as independent. Also, a more appropriate test would be something like a Chi-squared test or Fisher's exact test. Also, no error bars are included on the stacked bar graphs making interpretation impossible. Ultimately this is severely flawed and also appears to show very small differences which may be statistically different but may not represent biologically important findings. This would need further study.

      We appreciate the reviewer’s insightful comments regarding the interpretation of the biological data in Figure 3. 

      To clarify, each imaged position is considered an independent biological replicate (n = 18 from a total of 6 mice). We acknowledge that the description of the statistical methods and the experimental units was not sufficiently clear in the previous version. In our original submission, we used an ANOVA to test whether the proportion of each behavioral cluster differed across the tumor microenvironment regions. Post hoc pairwise comparisons were performed using Tukey’s test, with the results shown in Supplementary Figure 2d (currently Fig 3d). However, we agree with the reviewer that this approach may be misleading when paired with stacked bar plots that lack error bars, as it can obscure individual variability and does not explicitly represent statistical uncertainty.

      In the revised manuscript, we present the data as boxplots with individual data points, where each dot represents an imaged position, and the shape corresponds to a specific mouse. In Figure 3 d the y-axis displays the normalized percentage of each cluster across TME regions, expressed as z-scores. This normalization corrects for inter-mouse variability and facilitates a comparison of the relative distribution of clusters across TME regions, independent of the overall abundance differences between mice. We performed an ANOVA with Tukey's post hoc test for each individual behavioral cluster to assess differences across TME regions. Additionally, for transparency, in Supplementary Figure 5 d we provide the raw percentage values. The legends provide the number of positions and mice included in the analysis. 

      Comment#3:  Figure 4 has similar statistical issues in that the n is not listed and, again, it is unclear whether they are treating each cell track as independent which, again, would be inappropriate. The best practice for this type of data would be the use of super plots as outlined in Lord et al. (2020) JCI - SuperPlots: Communicating reproducibility and variability in cell biology.

      We appreciate the reviewer’s comments and suggestions regarding Figure 4. In this case as we are comparing overall the behavioral clusters features, each individual cell is treated as a unit. In the revised manuscript, we have clarified this point in the figure legend and incorporated plots in Figure 4c and 4e, indicating the mouse and imaging position each data point originates from. This enhances the visualization of reproducibility and variability in our data, demonstrating that the results are consistent across multiple mice and positions and are not driven by a single mouse or imaging position.

      Comment#4: The main issue that this raises is that the large-scale phenotyping module and the heterogeneity module appear designed to produce these statistical analyses that are used in these figures and, if they are based on the assumption that each track is independent, then this will produce inappropriate analyses as a default.

      We appreciate the reviewer’s comment, although we are unclear about the specific concern being raised. To clarify, in our large-scale phenotyping analysis, each position is assigned to a TME niche based on the CytoMAP analysis and the workflow outlined in Figure 3c. Multiple positions are imaged per mouse. For each position, we measure the proportion of tumor cells exhibiting a specific behavioral phenotype, and these proportions are subsequently used for statistical analysis (Figure 3 d). 

      In contrast, in Supplementary Fig. 5e-g, we treat each cell track as an individual unit, grouping them by their assigned large-scale region. Here, we assess whether differences between regions can be detected using a conventional single-feature analysis—a more traditional approach. However, we find that this method loses important behavioral patterns and distinctions that BEHAV3D-TP captures.

      We hope that this explanation, along with the modifications made to the figures and figure legends, provides greater clarity.  

      Reviewer #3 (Public review):

      Comment #1: The most challenging task of analyzing 3D time-lapse imaging data is to accurately segment and track the individual cells in 3D over a long time duration. BEHAV3D Tumor Profiler did not provide any new advancement in this regard, and instead relies on commercial software, Imaris, for this critical step. Imaris is known to have a very high error rate when used for analyzing 3D time-lapse data. In the Methods section, the authors themselves stated that "Tumor cell tracks were manually corrected to ensure accurate tracking". Based on our own experience of using Imaris, such manual correction is tedious and often required for every time step of the movie. Therefore, Imaris is not a satisfactory tool for analyzing 3D time-lapse data. Moreover, Imaris is expensive and many research labs probably can't afford to buy it. The fact that BEHAV3D Tumor Profiler critically depends on the faulty ImarisTrack module makes it unclear whether the BEHAV3D tool or the results are reliable.

      If the authors want to "democratize the analysis of heterogeneous cancer cell behaviors", they should perform image segmentation and tracking using open-source codes (e.g., Cellpose, Stardisk & 3DCellTracker) and not rely on the expensive and inaccurate ImarisTrack Module for the image analysis step of BEHAV3D.

      We appreciate the reviewer’s comments on the challenges of segmenting and tracking individual cells in 3D time-lapse imaging data. As mentioned previously (please refer to comment #1 to reviewer #1), our primary focus is to develop an analytical tool for comprehensive data analysis rather than developing tools for image processing. However to enhance accessibility, we have updated our tool to support data formats from open-source Fiji plugins, such as TrackMate, which will benefit users without access to commercial software (https://github.com/imAIgeneDream3D/BEHAV3D_Tumor_Profiler?tab=readme-ov-file#data-input ). In Supplementary Figures 1, 2, and 3, we present IVM data from different sources, processed using three distinct methods: MTrackJ (Supplementary Fig. 1), Cellpose + TrackMate (Supplementary Fig. 2), and µSAM + TrackMate (Supplementary Fig. 3). The latter two represent state-of-the-art deep learning approaches.

      On the other hand, while we recognize the limitations of Imaris, it remains widely used in the intravital microscopy community due to its user-friendly interface for 3D visualization and semi-automated segmentation capabilities. Since no perfect tracking method currently exists, we initially utilized Imaris for its ability to allow manual correction of faulty tracks, ensuring the reliability of our results. This approach, not only widely used (see above) but was the best available option when we began our analysis, allowing us to obtain accurate results efficiently.

      In the revised manuscript, we clarify the scope of our study and provide information on both Imaris and alternative processing options to strengthen the reliability of our findings:

      In introduction: “While significant efforts have been made to develop opensource segmentation and tracking tools for live imaging data, including IVM22–27 fewer tools exist for the unbiased analysis of tumor dynamics. One major barrier is that implementing such analytical methods often requires substantial computational expertise, limiting accessibility for many biomedical researchers conducting IVM experiments. To bridge this gap, we present BEHAV3D Tumor Profiler (BEHAV3D-TP)  by providing a robust, user-friendly tool that allows researchers to extract meaningful insights from dynamic cellular behaviors without requiring advanced programming skills.”

      In the Methods, we describe now describe not only Imaris processing pipeline, but also the µSAM segmentation pipelines and reference to CellPose IVM processing, which are combined with TrackMate for tracking. Additionally, to integrate morphological information from µSAM with tracking data from TrackMate, we developed a web tool to merge the outputs from both processing steps: https://morphotrack-merger.streamlit.app/  

      Comment #2: The authors developed a "Heterogeneity module" to extract distinctive tumor migratory phenotypes from the cell tracks quantified by Imaris. The cell tracks of the individual tumor cells are all quite short, indicating relatively low motility of the tumor cells. It's unclear whether such short migratory tracks are sufficient to warrant the PCA analysis to identify the 7 distinctive migratory phenotypes shown in Figure 2d. It's also unclear whether these 7 migratory phenotypes correspond to unique functional phenotypes.  

      For the 7 distinctive motility clusters, the authors should provide a more detailed analysis of the differences between them. It's unclear whether the difference in retreating, slow retreating, erratic, static, slow, slow invading, and invading correspond to functional difference of the tumor cells.

      While some tumor cells exhibit limited motility, indicated by short tracks, others demonstrate significant migratory capabilities (Figure 2 Invading and Retreating cells). This variability in tumor cell behavior is a central focus of our analysis, and our tool is specifically designed to identify and distinguish these differences. Our PCA analysis effectively captures this variability, as illustrated in Figure 2 d-f. It differentiates between cells exhibiting varying degrees of migratory behavior, including both highly and less migratory phenotypes, as well as their directionality relative to the tumor core and the persistence of their movements. Thus, we believe that our approach provides valuable insights into the distinct migratory phenotypes within the tumor microenvironment. 

      While our current manuscript does not provide explicit evidence linking each motility cluster to functional differences among the tumor cells, it is important to note that the state of the field supports the idea that cell dynamics can predict cell states and phenotypes. Research conducted by ourselves (Dekkers, Alieva et al., Nat Biotech, 2023) and others, such as Craiciuc et al. (Nature, 2022) and Freckmann et al. (Nat Comm, 2022) has shown that variations in cell motility patterns are indicative of underlying functional characteristics. For instance, cell morphodynamic features have been shown to reflect differences in cell types, T cell targeting states (Dekkers, Alieva et al., Nat Biotech, 2023), immune cell types (Crainiciuc et al. (Nature, 2022)), tumor metastatic potential, and drug resistance states (Freckmann et al. (Nat Comm, 2022)). In the revised manuscript, we have referenced relevant studies to underscore the biological significance of these behaviors. By doing so, we hope to clarify the potential implications of our findings and strengthen the overall narrative of our research:

      In discussion: “While our current study does not provide direct functional validation of the distinct motility clusters identified, existing literature strongly supports the notion that cell dynamics can serve as a proxy for functional states and phenotypic heterogeneity. Prior work, including studies by our group[19,66]  as well as Crainiciuc et al.[35] and Freckmann et al.[20], has demonstrated that variations in cell motility patterns can reflect underlying functional characteristics. Specifically, cell morpho-dynamic features have been shown to correlate with differences in cell type identity, T-cell engagement, metastatic potential, and drug resistance states. This growing body of evidence suggests that tumor cell behavior, as captured by BEHAV3D-TP, may serve as a predictive tool for deciphering functional tumor heterogeneity. Future studies integrating transcriptomic or proteomic profiling of motility-defined subpopulations could further elucidate the biological significance of these behavioral phenotypes.”

      Comment #3: Using only motility to classify tumor cell behaviours in the tumor microenvironment (TME) is probably not sufficient to capture the tumor cell difference. There are also other non-tumor cell types in the TME. If the authors aim to develop a computational tool that can elucidate tumor cell behaviors in the TME, they should consider other tumor cell features, e.g., morphology, proliferation state, and tumor cell interaction with other cell types, e.g., fibroblasts and distinct immune cells.

      The authors should expand the scale of tumor behavior features to classify the tumor phenotype clusters, e.g., to include tumor morphology, proliferation state, and tumor cell interaction with other TME cell types.

      We believe that using dynamic features alone is sufficient to capture differences in tumor behavior, as demonstrated by our results in Figure 2. However, we appreciate the reviewer’s suggestion to consider additional features, such as cell morphology, to finetune our analyses. To this end, we have adapted our pipeline to be compatible with any dynamic, morphologic or spatial features present in the data. In the revised manuscript we showcase this new addition with the analyses of two new dataset: 2D IVM data from healthy epithelial breast cells (Supplementary Fig 2) and 3D IVM data from adult gliomas (Supplementary Fig 3). These analyses identified cells with specific morphodynamic characteristics, which exhibited distinct kinetic behaviors or spatial distributions.

      However, we would like to point out that not all features may provide informative insights and that a wide range of features can instead introduce biologically irrelevant noise, making interpretation more challenging. For instance, in 3D microscopy, the zaxis resolution is typically lower, which can lead to artifacts like elongation in that direction. Adding morphological features that capture this may skew the analysis. Therefore, we believe that incorporating additional features should be approached with caution. We clarify these considerations in the revised manuscript to better guide users in utilizing our computational tool effectively:

      In discussion: “In addition to motility-based classification, features such as tumor cell morphology, proliferation state, and interactions with the tumor microenvironment can further refine tumor phenotyping. BEHAV3D-TP allows for the selection of diverse feature types, supporting datasets that include both dynamic, morphological and spatial parameters. However, we recognize that expanding the feature set may introduce biologically irrelevant noise, particularly in 3D microscopy data where limited z-axis resolution can lead to morphological artifacts. This highlights the potential need in the future to include unbiased feature selection strategies, such as bootstrapping methods67, to ensure the identification of meaningful and biologically relevant parameters. Careful consideration of these aspects is key to maximizing the interpretability and predictive value of analyses performed with BEHAV3D-TP.”

      Comment #4: The authors have already published two papers on BEHAV3D [Alieva M et al. Nat Protoc. 2024 Jul;19(7): 2052-2084; Dekkers JF, et al. Nat Biotechnol. 2023 Jan;41(1):60-69]. Although the previous two papers used BEHAV3D to analyze T cells, the basic pipeline and computational steps are similar, in particular regarding cell segmentation and tracking. The addition of a "Heterogeneity module" based on PCA analysis does not make a significant advancement in terms of image analysis and quantification.

      We want to emphasize that we have no intention of duplicating our previous publications. In this manuscript, we have consistently cited our foundational papers, where BEHAV3D was first developed for T cell migratory analysis in in vitro settings. In the introduction, we clearly state that our earlier work inspired us to adopt a similar approach for analyzing cell behavior in intravital microscopy (IVM) data, addressing the specific needs and complexities of analyzing tumor cell behaviors in the tumor microenvironment.

      Importantly, our new work provides several key advancements: 1) a pipeline specifically adapted for intravital microscopy (IVM) data; 2) integration of spatial characteristics from both large-scale and small-scale phenotyping; and 3) a zero-code approach designed to empower researchers without coding skills to effectively utilize the tool. We believe that these enhancements represent meaningful progress in the analysis of cell behaviors within the tumor microenvironment which will be valuable for the IVM community. We ensure that these points are clearly articulated in the revised manuscript:

      In introduction: “In line with this concept of characterizing cellular dynamic properties for cell classification, we have previously developed an analytical platform termed BEHAV3D 19,21 allowing to perform behavioral phenotyping of engineered T cells targeting cancer. While BEHAV3D was initially developed to analyze T cell migratory behavior under controlled in vitro conditions, we sought to expand its application to investigate tumor cell behaviors in IVM data, where the complexity of the TME presents distinct analytical challenges. This manuscript builds on our foundational work but represents a significant advancement by adapting the pipeline specifically for IVM datasets.”

      Reviewer #3 (Recommendations for the authors): 

      (1) If the authors want to "democratize the analysis of heterogeneous cancer cell behaviors", they should perform image segmentation and tracking using open-source codes (e.g., Cellpose, Stardisk & 3DCellTracker) and not rely on the expensive and inaccurate ImarisTrack Module for the image analysis step of BEHAV3D. 

      We thank the reviewer for this recommendation and as stated above we recognize that enhancing our pipeline's compatibility with open-source options is important. To this end, we have updated our tool to support data formats generated by open-source Fiji plugins like TrackMate, MTrackJ, and ManualTracking, improving compatibility with various segmentation and tracking pipelines (https://github.com/imAIgeneDream3D/BEHAV3D_Tumor_Profiler?tab=readme-ov-file#data-input ). In the revised manuscript, we detail this new functionality and demonstrate the operation of the BEHAV3D-TP heterogeneity module using an example dataset of glioma tumors.

      Additionally, we have updated the introduction to better clarify the scope of our study (See comment #1 from Review #3) and include references to existing image processing solutions.

      (2) For the 7 distinctive motility clusters, the authors should provide a more detailed analysis of the differences between them. It's unclear whether the difference in retreating, slow retreating, erratic, static, slow, slow invading, and invading correspond to functional difference of the tumor cells. 

      As noted in the comment above, the revised manuscript now incorporates references to relevant literature that support our understanding that behavioral differences among cells are driven by their underlying functional differences (See comment #2 from Reviewer #3). Additionally, we would like to point to Figure 2d and Supplementary Fig 4 c that provide evidence of the functional distinctions between the identified clusters.

      (3) The authors should expand the scale of tumor behavior features to classify the tumor phenotype clusters, e.g., to include tumor morphology, proliferation state, and tumor cell interaction with other TME cell types.

      We thank the reviewer for this valuable suggestion. In the revised manuscript, we have added the flexibility to incorporate a wide range of features, including morphological ones, and enabled users to select the specific features they wish to include in their analysis. To illustrate this functionality, we have included 2 example dataset analyzed using this approach (See comment #3 from Reviewer #3). Additionally, as indicated above we emphasize the importance of careful selection and interpretation of features, as improper choices may lead to biologically irrelevant results. This clarification is intended to ensure that users apply the tool thoughtfully and derive meaningful insights.

    1. Author response:

      The following is the authors’ response to the original reviews

      Reviewer #1 (Public review):

      We thank reviewer 1 for the helpful comments. As indicated in the responses below, we have taken all comments and suggestions into consideration in this revised version of the manuscript.

      Weaknesses:

      While this study convincingly describes the phenotype seen upon Drp1 loss, my major concern is that the mechanism underlying these defects in zygotes remains unclear. The authors refer to mitochondrial fragmentation as the mechanism ensuring organelle positioning and partitioning into functional daughters during the first embryonic cleavage. However, could Drp1 have a role beyond mitochondrial fission in zygotes? I raise these concerns because, as opposed to other Drp1 KO models (including those in oocytes) which lead to hyperfused/tubular mitochondria, Drp1 loss in zygotes appears to generate enlarged yet not tubular mitochondria. Lastly, while the authors discard the role of mitochondrial transport in the clustering observed, more refined experiments should be performed to reach that conclusion.

      It would be difficult to answer from this study whether Drp1 plays a role beyond mitochondrial fission in zygotes. However, the reasons why Drp1 KO zygotes differ from the somatic Drp1 KO model can be discussed as follows.

      First, the reviewer mentioned that the loss of Drp1 in oocytes leads to hyperfused/tubular mitochondria, but in fact, unlike in somatic cells, the EM images in Drp1 KO oocytes show enlarged mitochondria rather than tubular structures (Udagawa et al., Curr Biol. 2014, PMID: 25264261, Fig. 2C and Fig. S1B-D), as in the case of zygotes in this study. Mitochondria in oocytes/zygotes have the shape of a small sphere with an irregular cristae located peripherally. These structural features may be the cause of insensitivity or resistance to inner membrane fusion the resultant failure to form tubular mitochondria as seen in somatic cell models. Nonetheless, quantitative analysis of EM images in the revised version confirmed that the mitochondria of Drp1-depleted embryos were not only enlarged but also significantly elongated (Figure 2J-2M). Therefore, in Drp1-depleted embryos, significant structural and functional (e.g., asymmetry between daughters) changes in mitochondria were observed, and these are expected to lead to defects in the embryonic development.

      As for mitochondrial transport, we do not fully understand the intent of this question, but we do not entirely rule out mitochondrial transport. At least clustered mitochondria did not disperse again, but how mitochondria behave through the cytoskeleton within clusters will require further study, as the reviewer pointed out.

      Reviewer #1 (Recommendations For The Authors):

      (1) The authors show no effect of Myo19 Trim-Away, yet it remains unclear whether myo19 is involved in the positioning of mitochondria around the spindle. Judging by their co-localization during that stage, it might be. Therefore, in the absence of myo19, mitochondria might remain evenly distributed throughout mitosis, thus passively resulting in equal partitioning to daughter cells, with no severe developmental defects. Could the authors show a video of the whole process and discuss it?

      We have newly performed live imaging of mitochondria and chromosomes in Myo19 Trim-Away zygotes (n=13). As shown in Figure 1-figure supplement 2 and Figure 1-Video 2, there were no obvious changes in mitochondrial (and chromosomal) dynamics throughout the first cleavage and no significant mitochondrial asymmetry was observed, Therefore, we conclude that depletion of Myo19 does not cause mitochondrial asymmetry during embryonic cleavage. These results are described in the revised manuscript (Line 218-221).

      (2) Mitochondrial aggregation upon Drp1 depletion should be characterized in more detail: for example, % of mitochondria free, % in small clusters (> X diameter), and % in big clusters (>Y diameter).

      In the revised version, mitochondrial aggregation has been quantified by comparing the cluster size and number in control, Drp1 Trim-Away and Drp1 Trim-Away embryos expressing exogenous Drp1 (mCh-Drp1) (Figure 2G, 2H). In control embryos, mitochondria were interspersed in a large number of small clusters, while in Drp1-depleted embryos, mitochondria became highly aggregated into a small number of large clusters that was reversed by expression of mCh-Drp1. These results are described in the revised manuscript (Line 242-245).

      (3) The discrepancies with parthenogenetic embryos derived from Drp1 (-/-) parthenotes should be commented on. Quantification of the dimensions of the clusters would help establish the degree of similarity/difference. Could the authors comment on their hypothesis as to why the clusters are remarkably larger in Drp1 depleted zygotes?

      In the revised version, we have quantified the mitochondrial aggregation in Drp1 KO parthenotes (Figure 2-figure supplement 1; the data for Drp1 KO parthenotes has been reorganized into the supplemental figure, due to lack of space in figure 2 caused by the addition of quantitative data for Drp1 Trim-Away embryos). The size of mitochondrial clusters in Drp1 KO parthenotes was significantly increased compared to controls, but as the reviewer noted, mitochondrial aggregation appears to be moderate compared to that in Drp1-depleted embryos. The phenotypic discrepancies in two Drp1-deficient embryo models is discussed below.

      First, it is clear that phenotypic severity of Drp1 KO oocytes is dependent on the age of the female. Indeed, oocytes collected from 8-week-old female arrested meiosis after NEB, mainly due to marked mitochondrial aggregation (Udagawa et al., Curr Biol. 2014, PMID: 25264261), whereas oocytes from juvenile female completed meiosis (Adhikari et al., Sci Adv. 2022, PMID: 35704569), and thus Drp1 KO pathenotes were obtained from juvenile female in the present study. Comparison of mitochondrial morphology in Drp1 KO oocytes in both papers also suggests that mitochondrial aggregation in adult mice is more intense (Udagawa et al., Curr Biol. Fig. 2A) than in juvenile mice (Adhikari et al., Sci Adv. 2022: Fig. 1G, 1H), and appears to be similar to Drp1-depleted embryos in this study (Figure 2E). There may be differences in the level of Drp1 depletion in these Drp1-deficient oocytes/zygotes. Similar results occurring between juvenile and adult KO female have been reported in a previous paper (Yueh et al., Development 2021, PMID: 34935904), as adult-derived Smac3<sup>Δ/Δ<?sup> zygotes arrested at the 2-cell stage, whereas juvenile-derived Smac3<sup>Δ/Δ<?sup> zygotes have developmental competence comparable to the wild type. Remarkably, the SMC3 protein levels in juvenile Smac3<sup>Δ/Δ<?sup> oocytes was also comparable to Smc3<sup>fl/fl</sup>. The authors surmised that the decline maternal SMC3 between juvenile and sexual maturity is probably due to the continuous induction of the promoter-Cre driver, suggesting that similar induction may also occur in Drp1 KO oocytes. In addition, we also observed not only age differences but also batch differences in Drp1 KO oocytes (and resulting embryos) such that little mitochondrial aggregation was observed in oocytes collected from some juvenile KO colonies. Therefore, for KO models showing age (sexual maturation)-dependent gradual phenotypic changes, Trim-way may be an approach that provides more reproducible results as it induces acute degradation of maternal proteins.

      (4) Mitochondrial clusters in Drp1 trim-away zygotes resemble those seen when defects in mitochondrial positioning are obtained by TRAK2 induction (PMID: 38917013), pointing again to a role of actin in the clustering process. Could the authors explore the role of actin further?

      TRAK2 and microtubule-dependent mechanisms may also be involved in mitochondrial dynamics during the first cleavage division, possibly in association with migration of two pronuclei. Although the mitochondrial aggregation induced by TRAK2 overexpression is similar to that in Drp1-depleted embryos, it is unlikely that changes at the EM level occurred as seen in Drp1-depleted embryos (enlarged mitochondria, etc.). In addition, in TRAK2-overexpressing embryos, rather than uneven partitioning of mitochondria, the daughter blatomeres themselves were uneven in size after cleavage, making it difficult to precisely assess the similarity between the two models.

      Regarding the role of F-actin, we show that the subcellular distribution of cytoplasmic actin overlaps with that of mitochondria throughout the first cleavage and seems to accumulate in aggregated mitochondria, particularly during the mitotic phase, as higher correlation was observed (Figure 1E). Although it was not observed that actin and the myo19 motor regulate mitochondrial partitioning, as reported in somatic cell-based studies, it is possible that actin accumulated in mitochondria may be indirectly involved in mitochondrial dynamics via mitochondrial fission. For example, inverted formin 2 (INF2) enhance actin polymerization and is required for efficient mitochondrial fission as an upstream function of Drp1 (Korobova et al., Science 2013, PMID: 23349293). In the revised manuscript, we have added the description on this point. (Line 452-456)

      (5) Electron microscopy images showed indeed aberrant morphology of the mitochondria, yet not a hyperfused morphology. Aspect ratio (long/short axis) quantification should be included, besides the current measurement, since mitochondria in Drp1 trim-away look bigger yet as round as in the control.

      In the revised version, detailed quantitative data on EM images has been added (Figure 2J-2M). In Drp1 depleted embryos, significant increases were observed in both the major and minor axes of mitochondria. As the reviewer noted, we also assumed that mitochondria in depleted embryos were enlarged rather than elongated, but the quantification of aspect ratio shows that significant elongation occurred. These results has been described in the revised manuscript (Line 252-256).

      (6) Why are mitochondria in golgi-mcherry-expressing cells showing a different morphology of the clusters?

      As noted by the reviewer, compared to other mitochondrial images, Drp1-depleted embryos expressing Golgi-mCherry appear to have less mitochondrial aggregation. The exact reason is not known, but may be due to inter-lot variation of Trim21 mRNA used in this experiment. Nevertheless, substantial mitochondrial aggregation was observed compared to the control, which does not seem to affect the conclusion.

      (7) Authors comment on ROS being enriched (highly accumulated) in mitochondria. However, while quantification is missing, it might seem that ROS are equally distributed in control or Drp1 Trim-Away embryos. Could the authors quantify ROS signal inside and outside of the mitochondria, perhaps using a mask drawn by mitotracker? Furthermore, it would make these data more convincing to artificially induce/deplete ROS to validate the sensitivity of the technique to variations. Also, why is ROS pattern referred to as ectopic?

      Thank you for your useful suggestions. In the revised version, masked binary images were created from mitochondrial images to quantify ROS levels inside and outside mitochondria (Line 734-741). The result shows the accumulation of ROS to mitochondria in Drp1-depleted embryos (Figure 4-figure supplement 1E). The term ectopic was used to mean excessive accumulation of ROS in the mitochondria compared to normal embryos, but has been deleted as it is not very accurate.

      Minor comments:

      (A) Video 1: images at t=-00:20 and t=00:00 of the mtGFP are actually the same images as H2B-mCherry.

      Probably a faulty filter/shutter control failed to capture GFP fluorescence at these times. It appears that the autocontrast function detected a small amount of mCherry fluorescence leakage. It would be possible to replace it with another video, but as the relevant frame were unrelated to the analysis, the previous video was used as is. The same problem also occurs in the newly added Myo19-depleted zygote movie (Figure 1-Video 2, 03:15).

      (B) Could you calculate the degree of colocalization between mt-GFP and ER-mCherry in ctrl and Drp1 trim-away? While it is apparent that ER is somehow more associated with mitochondrial clusters, it would be informative to quantify it.

      Since the ER is partially confined to the mitochondrial aggregation site, it was difficult to calculate correlation coefficients from fluorescence images of mt-GFP and ER-mCherry to quantitatively assess colocalization. Instead, line scan analysis of whole mitochondrial clumps showed that the peak of the ER-mCherry signal overlaps with that of mt-GFP, but this is not the case for Golgi-mCherry or peroxisome-mCherry (Figure 2-figure supplement 2A-2C).

      (C) Regarding the developmental arrest: The quantification of the different stages at each developmental time could be more informative. For example, at E4.5 how many embryos are at each stage (2-cell, 4-cell, ... blastocyst)? Also, could the authors comment on the reduction in developmental competence in Figure 4C, regarding the blastocyst stage?

      Many arrested embryos do not maintain their morphologies and undergo a unique degenerative process over time, known as cell fragmentation. Therefore, it is difficult to accurately determine the number of each developmental stage at, for example, E4.5 days. In this study, the 2-cell stage was observed at E1.5, the 4-8 cell at E2.5-E3.0, morula at E3.5 and the blastocyst at E4.5.

      Although the rate of embryos reaching the blastocyst stage was reduced compared to that of normal embryos, the overexpression of mCh-Drp1 may explain the failure of complete restoration of developmental competence, since embryos injected solely with mCh-Drp1 mRNA also showed reduced developmental competence. For rescue experiments, the comparison with internal controls is more important and therefore we described below. This is a specific effect of Drp1 deletion because none of the internal control conditions increased arrest at the 2-cell stage and arrest was completely reversed by microinjecting Trim-away insensitive exogenous mCh-Drp1 mRNA (Line 337-340).

      (D) In lines 103 to 105, proliferation should be changed to division or development.

      In the revised version, proliferation has been changed to division (Line 103).

      (E) Could the authors reference the statement in lines 168-169?

      The following 3 references have been added (Hardy et al., 1993, PMID: 8410824; Meriano et al., 2004, PMID: 15588469; Seikkula et al., 2018, PMID: 29525505).

      (F) Line 448: "Cells lacking Drp1 have highly elongated mitochondria that cannot be divided into transportable units,..." This is clearly not the case for zygotes, so why are then these mitochondria still clustering and not transported elsewhere?

      Although it is difficult to answer this reviewer's question precisely, EM images of Drp1-depleted embryos suggest that individual mitochondria appear not only to be enlarged but also to have increased outer membrane attachment due to excessive aggregation. Thus, these large mitochondrial clumps may therefore be preventing transport.

      Reviewer #2 (Public review):

      We thank reviewer 2 for the helpful comments. As indicated in the responses below, we have taken all comments and suggestions into consideration in this revised version of the manuscript.

      Weaknesses:

      The authors first describe the redistribution of mitochondria during normal development, followed by alterations induced by Drp1 depletion. It would be useful to indicate the time post-hCG for imaging of fertilised zygotes (first paragraph of the results/Figure 1) to compare with subsequent Drp1 depletion experiments.

      In the revised version, the time after hCG has been indicated (Line 176-182). In subsequent Drp1 depletion experiments, the revised version notes that “no significant delay in cell cycle progression was observed following Drp1 depletion (data not shown) compared to control embryos (Figure 1A)” (Line 291-193). There was a slight discrepancy in the time post-hCG between live imaging and immunofluorescence analysis (Figure 1-figure supplement 1A), which may be due to manipulation of zygotes outside incubator during the microinjection of mRNA.

      It is noted that Drp1 protein levels were undetectable 5h post-injection, suggesting earlier times were not examined, yet in Figure 3A it would seem that aggregation has occurred within 2 hours (relative to Figure 1).

      As the reviewer pointed out, the depletion of Drp1 is likely to have occurred at an earlier stage. In this study, due to the injection of various mRNAs to visualize organelles such as mitochondria and chromosomes, observations were started after about 5 h of incubation for their fluorescent proteins to be sufficiently expressed. Therefore, for the Western blot analysis, samples were prepared according to the time of the start of the observation.

      Mitochondria appear to be slightly more aggregated in Drp1 fl/fl embryos than in control, though comparison with untreated controls does not appear to have been undertaken. There also appears to be some variability in mitochondrial aggregation patterns following Drp1 depletion (Figure 2-suppl 1 B) which are not discussed.

      In the revised version, mitochondrial aggregation has been quantified by comparing the cluster size and number in control, Drp1 Trim-Away and Drp1 Trim-Away embryos expressing exogenous Drp1 (mCh-Drp1) (Figure 2G, 2H). We have also quantified the mitochondrial aggregation in Drp1<sup>fl/fl</sup> and Drp1<sup>Δ/Δ</sup> parhenotes (Figure 2-figure supplement 1; note that the data for Drp1 KO parthenotes has been reorganized into the supplemental figure, due to lack of space in figure 2 caused by the addition of quantitative data for Drp1 Trim-Away embryos). Mitochondria appear to be slightly more aggregated in Drp1<sup>fl/fl</sup> embryos than in control, but no significant differences in cluster size or number were observed (data not shown). On the other hand, mitochondrial clusters in Drp1 Trim-Away embryos were remarkably larger than Drp1<sup>Δ/Δ</sup> parhenotes, Please refer to the response to reviewer 1's comment (3) for discussion of this discrepancy.

      As noted by the reviewer, compared to other mitochondrial images, Drp1-depleted embryos expressing Golgi-mCherry appear to have less mitochondrial aggregation. The exact reason is not known, but may be due to inter-lot variation of Trim21 mRNA used in this experiment. Nevertheless, substantial mitochondrial aggregation was observed compared to the control, which does not seem to affect the conclusion.

      The authors use western blotting to validate the depletion of Drp1, however do not quantify band intensity. It is also unclear whether pooled embryo samples were used for western blot analysis.

      In the revised version, the band intensities in Western blot analysis were quantified and validated the previous results (Figure 1H for Myo19 depletion, Figure 2B for Drp1 expression during preimplantation development, Figure 2D for Drp1 depletion). The number of embryos analyzed was described in Figure legends (Pooled samples ranging from 20 to 100 were used).

      Likewise, intracellular ROS levels are examined however quantification is not provided. It is therefore unclear whether 'highly accumulated levels' are of significance or related to Drp1 depletion.

      In the revised version, masked binary images were created from mitochondrial images to quantify ROS levels inside and outside mitochondria (Line 734-741). The result shows the accumulation of ROS to mitochondria in Drp1-depleted embryos (Figure 4-figure supplement 1E).

      In previous work, Drp1 was found to have a role as a spindle assembly checkpoint (SAC) protein. It is therefore unclear from the experiments performed whether aggregation of mitochondria separating the pronuclei physically (or other aspects of mitochondrial function) prevents appropriate chromosome segregation or whether Drp1 is acting directly on the SAC.

      In the revised manuscript, we have discussed this reference (Zhou et al., Nature Communications, PMID: 36513638) (Line 482-483).

      Reviewer #2 (Recommendations For The Authors):

      The authors report that disruption of F-actin organization led to asymmetry in mitochondrial inheritance, however depletion of Myo19 does not impact inheritance. The authors note in the discussion that loss of another mitochondrial motor protein, Miro, has been shown to affect mitochondrial inheritance. They suggest this may be due to reduced levels of Myo19, despite data from the present study suggesting a lack of involvement of Myo19. Given that Miro1 also interacts with microtubules, and crosstalk between actin filaments and microtubules has been reported, have the authors considered whether other motor proteins, such as KIF5, may be involved in mitochondrial movement in the zygote and therefore inheritance? Myo19 also plays a role in mitochondrial architecture. Were any differences noted at the EM level?

      During oocyte meiosis and early embryonic cleavage, kinesin-5 has been reported to be important for the formation of bipolar spindles (Fitzharris, Curr Biol., 2009, PMID: 19465601) and may have some involvement in mitochondrial dynamics. Given that the migration of two pronuclei towards the zygotic centre is dynein-dependent manner (Scheffler Nat Commun. 2021PMID: 33547291), dynein may also be involved in the process of mitochondrial accumulation around the pronuclei. Nevertheless, whether microtubule-dependent mechanisms regulate mitochondrial partitioning remains controversial. Mitochondria basically diverge from microtubules at the onset of mitosis, and indeed Miro1-deleted zygotes did not show the asymmetric mitochondrial partitioning (Lee et al., Front Cell Dev Biol. 2022, PMID: 36325364). More recently, it was reported that overexpression of TRAK2 causes significant mitochondrial aggregation in embryos (Lee et al., Proc Natl Acad Sci U S A. 2024, PMID: 36325364), but since overexpression might disrupt a regulatory balance by other motors/adaptor complexes, further investigation using TRAK2-deficient embryos is expected.

      As noted by the reviewer, myo19 seems to be important for the maintenance of mitochondrial cristae architecture and, consequently, for the regulation of mitochondrial function (Shi et al., Nat Commun. 2022, PMID: 35562374). We have not observed the EM images in myo19-depleted embryos, but we examined their membrane potential and ROS by TMRM and H2DCF staining, respectively, and confirmed that they were comparable to control embryos (data not shown). The loss of myo19 in zygotes/embryos did not cause any functional changes in mitochondria, suggesting that mitochondrial architecture may not be substantially affected either.

      Transcriptomic analysis would be useful to identify alterations in cell cycle checkpoint regulators, as well as immunofluorescence to identify changes in spindle assembly checkpoint protein recruitment.

      The present results showed that the majority of Drp1-depleted embryos arrest at the G2 stage, possibly due to cell cycle checkpoint mechanisms. Transcriptome analysis would certainly be beneficial, but eventually more detailed analysis of proteins and their phosphorylation modifications, etc. is needed for accurate assessment. These studies will be the subject of future work.

      Minor comments:

      There are many instances where the English could be improved, particularly the overuse of the word 'the'.

      We have checked the manuscript again carefully and hopefully it has been improved some.

      Line 144: replace 'took' with 'take'.

      We have corrected this in the revised version (Line 140).

      Line 157: it is unclear what is meant by 'hinders the functional importance of Drp1 in mature oocytes and embryos'.

      This description has been corrected to “complicates the functional analysis of Drp1 in mature oocytes and embryos” (Line 152-153)

      Line 198: replace with 'displayed a mitochondrial distribution pattern closely associated with'

      We have corrected this in the revised version (Line 195-196).

      Line 200: provide a time to clarify when the cytoplasmic meshwork was 'subsequently reorganized'

      In the revised version, “at the metaphase” has been added (Line 198).

      Line 204: replace 'to' with 'for'

      We have corrected this in the revised version (Line 203).

      Lines 285-87: consider rearranging the text to improve the flow.

      To improve the flow of text before and after, the following sentence has been added; We postulated that this asymmetry was due to non-uniformity in the distribution of mitochondria around the spindle (Line 295-297)

      Line 418: replace 'central' with 'centre'

      We have corrected this in the revised version (Line 430).

      Line 427: replace 'pertaining' with 'partitioning'

      We have corrected this in the revised version (Line 438).

      Line 574: clarify to what '1-5% of that of the oocytes' refers

      We have corrected it to “1-5% of the total volume of the zygote.” (Line 587-588).

      Line 619: indicate the dilution used

      We apologize for the previous incorrect description. We used a part of the extract as the template, not a dilution, and have corrected it to be accurate (Line 631-632).

      Line 634: replace 'on' with 'in' and detail in which medium embryos were mounted.

      We have corrected this in the revised version (Line 647).

      Please check all spelling in the figures.

      Figure 1J - inheritance is spelt incorrectly.

      Figure-Suppl 1, D: Interphase (PN) and (2-cell) is spelt incorrectly. G: inheritance is spelt incorrectly.

      Figure 5F - bottom section prior to cytokinesis, spindle is spelt 'spincle'

      Ensure consistency in abbreviation use (e.g. use of NEB and NEBD).

      Thank you for your careful correction of typographical errors. In the revised version, all points raised by the reviewers have been corrected.

      Reviewer #3 (Public review):

      We thank reviewer 2 for the helpful comments. As indicated in the responses below, we have taken all comments and suggestions into consideration in this revised version of the manuscript.

      Seemingly, there are few apparent shortcomings. Following are the specific comments to activate the further open discussion.

      Line 246: Comments on cristae morphology of mitochondria in Drp1-depleted embryos would better be added.

      In the revised manuscript, we have added the following comment; swollen or partially elongated mitochondria with lamella cristae structures in the inner membrane were observed in Drp1 depleted embryos. In addition, the quantification of aspect ratio (long/short axis) shows that significant mitochondrial elongation was occurred (Figure 2M). These results has been described in the revised manuscript (Line 251-256).

      - Regarding Figure 2H: If possible, a representative picture of Ateam would better be included in the figure. As the authors discussed in line 458, Ateam may be able to detect whether any alterations of local energy demand occurred in the Drp1-depleted embryos.

      Thank you for your very useful comments. Although it would be interesting to investigate whether alterations in ATP levels occurred in localized areas (e.g., around the spindle), the present study used conventional fluorescence microscope instead of confocal laser microscopy to observe ATeam fluorescence in order to quantify the fluorescence intensity in the whole embryo (or whole blastomere) and thus we currently cannot provide the images that reviewer expected. As shown in Figure-figure supplement 1C, the ATP levels tend to be higher at the cell periphery in control and at the mitochondrial aggregation areas in Drp1-depleted embryos, but it would need high resolution images using confocal microscopy to show it clearly.

      - Line 282: In Figure 3-Video 1, mitochondria were seemingly more aggregated around female pronucleus. Is it OK to understand that there is no gender preference of pronuclei being encircled by more aggregated mitochondria?

      Review of multiple videos shows that aggregated mitochondria were localized toward the cell center, but did not exhibit the behavior of preferentially concentrating near the female pronucleus.

      - Line 317: A little more explanation of the "variability" would be fine. Does that basically mean that the Ca<sup>2+</sup> response in both Drp1-depleted blastomeres were lower than control and blastomere with more highly aggregated mitochondria show severer phenotype compared to the other blastomere with fewer mito?

      We think that the reviewer's comments are mostly correct. It is clear that there is a bias in Ca<sup>2+</sup> store levels between blastomeres of Drp1 depleted embryos, However, since mitochondria were not stained simultaneously in this experiment, we cannot draw conclusions in detail, such that daughter blastomere that inherit more mitochondria have higher Ca<sup>2+</sup> stores, or that blastomere with more aggregated mitochondria have lower Ca<sup>2+</sup> stores.

      - Regarding Figure 5B (& Figure 1-figure supplement 1B): Do authors think that there would be less abnormalities in the embryos if Drp1 is trim-awayed after 2-cell or 4-cell, in which mitochondria are less involved in the spindle?

      The marked centration of mitochondrial clusters in Drp1-depleted embryos appears to be associated with migration of the pronuclei toward the cell center, which is unique to the first embryonic cleavage. Since the assembly of the male and female pronuclei at the cell center is also unique to the first cleavage, binucleation due to mitochondrial misplacement was observed only in the first cleavage. Therefore, if Drp1 is depleted at the 2-cell or 4-cell stage, chromosome segregation errors may be less frequent. However, since unequal partitioning of mitochondria is thought to occur, some abnormalities in embryonic development is likely to be observed.

      Reviewer #3 (Recommendations For The Authors):

      Specific comments

      - Line 262: "Since mitochondrial dynamics are spatially coordinated at the ER-mitochondria MCSs," adequate ref. would better be added.

      We have added an adequate reference to the revised manuscript (Friedman et al., 2011, PMID: 21885730).

      - Line 333-336: "...as assessed by the presence of the nuclear envelope." Do authors show the data? In Figure 4-figure supplement 1A, the difference of the phosphoH3-ser10 signal between control and Trim-Away group might be weak. For clarity, it would be helpful if authors indicate the different points to note in the figure.

      Although the data is not shown, nuclear staining of arrested 2-cell stage embryos exhibited clear nuclear membranes, similar to the DAPI image in Figure 4-figure supplement 1A. We have indicated that the data is not shown in the revised version (Line 345). Based on a report that phosphorylated histone H3 (Ser10) localizes in pericentromeric heterochromatin that hat can be visualized by DAPI staining in late G2 interphase cell (Hendzel et al., 1997, Chromosoma, PMID: 9362543), this study qualitatively estimated the G2 phase from the phosphorylated histone H3 signal and the DAPI counterstained images. We have noted this point in the revised figure legend (Line 1012-1014).

      Typos or points for reword/rephrase

      - Line 149: "molecular identification" may better be " molecular characteristics".

      We have corrected this in the revised version (Line 145).

      - Line 157: "hinders the functional importance" would be "implies the functional importance" or "complicates the functional analysis".

      We have corrected this in the revised version (Line 152-153).

      - Line 208: "Since the role of F-actin in many cellular events, such as cytokinesis, preclude them as targets for experimentally manipulating mitochondrial distribution, " may better be "Given many cellular roles, disruption of F-actin per se was unsuitable as a strategy for manipulating mitochondrial distribution", for example.

      We have corrected this in the revised version (Line 207-208).

      - Line 260: "with MCSs with the plasma.." may better be "with MCSs such as with the plasma..".

      We have corrected this in the revised version (Line 267-268).

      - Line 312: "distribution and segregation" may better be "distribution and the resulting segregation of the inter-organelle contacts".

      We have corrected this in the revised version (Line 324-325).

      - Line 427: "pertaining" might be "partitioning".

      We have corrected this in the revised version (Line 438).

      Line 463: "loss of Drp1 induced mitochondrial aggregation disturbs" may better be "mitochondrial aggregation induced by the loss of Drp1 disturbs".

      We have corrected this in the revised version (Line 478-479).

      - Line 752: "endoplasmic reticulum (pink) " would be " endoplasmic reticulum (aqua) ".

      We have corrected this in the revised version (Line 780).

      - Figure 5E: "(Noma 2-cell embryos)" would be "(Nomal 2-cell embryos)".

      - Figure 5F: "Mitochondrial centration prevents dual spincle assembly" would be "Mitochondrial centration prevents dual spindle assembly".

      Thank you for your careful correction of typographical errors. We have corrected all the words/expressions the reviewer pointed out in the revised version.

    1. Each circle identifies what students do. Students 1) imagine, examine, and perceive; 2) explore, experiment, and develop craft; 3) create; 4) reflect, assess, and revise, and 5) share their products with others. The arrows indicate the ways teachers can guide students through the creative process.

      From looking at this model, we can imply that arts integration is learner-centered. The teacher is guiding and the students are doing. The arrows (teachers) aren't the focus, the circles and words (students) are.

    1. Author response:

      The following is the authors’ response to the original reviews

      The main criticisms levied by both reviewers can be traced down to our use of a long-term video archive to assess for the effects of aging on individual chimpanzees over extended time periods. Specifically, the reviewers raised several points surrounding whether we could exclude ecological variation over years as the explanation of changes with aging, rather than aging itself. Whilst we acknowledge there are limitations to our approach, we provide a comprehensive response to these points highlighting:

      (1) Where ecological variables have been accounted for using controls (including the behaviors of other individuals, or an aging individuals’ behavior at younger ages).

      (2) Where ecological data may be missing, thus a potential limitation to our study, and further data would be beneficial.

      (3) Whether, in light of these limitations, interannual ecological variation offers a likely explanation for the behavioral changes we have identified. We provide an argument that whilst ecological data would be desirable for our study, interannual changes in ecology are unlikely to explain the trends in our data. Additionally, we explain why age-related changes, such as senescence, are more likely to underpin the patterns described in our manuscript.

      Across 1-3, we have made substantial changes to the reporting of our manuscript to ensure that our results are communicated transparently, and conclusions are made with appropriate care. We have also moved all discussion of coula-nut cracking to the supplementary materials, given the points raised by reviewers about the lack of data describing coula-nut cracking in earlier field seasons.

      We hope that these modifications will enhance both the editors’ and reviewers’ assessment of our manuscript, where we have aimed to make careful conclusions that are supported by our available data. Similarly, we have aimed to communicate the importance of our results across fields of research including primatology, evolutionary anthropology, and comparative gerontology, and hope that our research will be of use to further studies within these subfields.

      Reviewer 1 (Recommendations for the authors):

      (1) If possible, include results or a summary of the behaviour of younger adults using stone tools during the same period. It would be helpful to know if they had the same or different pattern to exclude other factors that may influence the tool use (harder nuts in a particular season, diseases, motivation for other foods, etc). 

      We include data for other individuals when analyzing attendance. However, we did not collect comparable long-term efficiency data on younger adult individuals for this study. This is, in part, due to the time constraints imposed by long-term behavior coding. Additionally, only one adult was both present at Bossou throughout the 1999-2016 period, and younger than the threshold for our old-age category across these years (thus, the baseline used to compare with older adults would be just one younger adult, thus would not have been useful for characterizing normal variation of many younger adults over time). However, given the longitudinal data we present, we can use data from the earlier field seasons for each elderly focal individual as a personalized baseline control. Previous studies at Bossou find that across the majority of adulthood, efficiency varies between individuals, but is stable within individuals over time (e.g., Berdugo et al. 2024, cited). We detected similar stability in individuals’ efficiency over the first three field seasons sampled in our analysis, where there was very little intra-individual variation in tool-using efficiency. However, in later years, two individuals (Velu & Yo) began to exhibit relatively large reductions in efficiency.

      These results are unlikely to be explained by ecological variation. If there was a change in ecology underpinning our results, we would expect: [1] changes in ecology to also introduce variation in earlier field seasons, and [2] to influence all individuals in our study similarly. As such, if the changes observed in later field seasons were due to ecological changes, they should have caused a reduced efficiency across individuals, and to a similar degree – we did not observe this result, with large reductions in efficiency were confined to two individuals.   Moreover, for Yo (the individual who exhibited the largest reduction in efficiency) we found some additional evidence that changes in oil-palm-nut cracking efficiency extended beyond the period we sampled, i.e. they were evident even in 2018, reflecting a long-term, directional reduction in efficiency as compared to earlier years of her life. This consistent reduction in tool-using efficiency over multiple years adds further weight to the hypothesis that changes at the level of the individual were causing reduced tool-using efficiency, rather than our results being underpinned by interseasonal variation in ecology.

      Whilst we agree that our study is limited in the extent to which we can analytically assess ecological explanations for changes in nut-cracking efficiency, we believe that hypothetical ecological changes across field seasons do not predict our results. We now raise both sides of this debate in our discussion, where we outline our limitations (see lines 535-593).

      (2) The data from 2011 was scarce, with only one individual having 10 encounters. It would be better to be cautious with this season's results. 

      We appreciate this limitation raised by the reviewer. Velu and Yo were only encountered a few times in 2011; however, both were encountered more frequently in 2016. For 2011, we did not collect oil-palm nut cracking data for either Yo or Velu. Thus, their change in efficiency was detected by models using data from all other years, regardless of the few encounters in 2011. This sparsity of data may still have influenced our metrics for the proportion of time chimpanzees spent engaging in different behaviors when present at the outdoor laboratory in 2011, particularly for Velu, who was one of the two individuals who exhibited a change in behavior in this year (along with Fana, N = 10 for 2011). We have therefore added a line in our results and discussion highlighting the sparsity of data for Velu when estimating these proportions for 2011 (see lines 255-256 & 410).

      Minor corrections 

      (1) The last paragraph of the introduction presents many results, which should be in the results section. 

      We would like to keep this section of the introduction. Our paper investigates the effect of aging on many different aspects of nut cracking, which could become confusing for readers unless laid out clearly. We believe that having a short summary early on in the paper assists readers with following the methods and arguments presented within our paper.

      (2) The first section (Sampled data) of the results contains much information that belongs in the methods section. 

      We appreciate that there is some overlap between our methods and results section. However as the results section comes before the methods in our manuscript, we wanted to ensure that there is suitable information in our results that allow our results to be interpreted clearly by readers, and that the methods used to generate these results are transparently communicated. For these reasons, we will leave this information in the results, as we believe it increases our paper’s readability. 

      Reviewer 2 (Public review):

      One of the main limitations of this study is the small sample size. There are only 5 of the old-aged individuals, which is not enough to draw any inferences about aging for chimpanzees more generally. Howard-Spink and colleagues also study data from only five of the 17 years of recorded data at Bossou. The selection of this subset of data requires clarification: why were these intervals chosen, why this number of data points, and how do we know that it provides a representative picture of the age-related changes of the full 17 years? 

      We note that our sample size is limited to 5 individuals. This is an inevitable constraint of analyzing aging longitudinally in long-lived species, as only few individuals will live to old age. We argue that 17 years is a long enough period of study, as in the initially sampled field season (1999) focal individuals are reaching a mature age of adulthood (39-44 years) and begin to age progressively up to ages that are typically considered to be on the extreme side for chimpanzees’ lifespans in the wild (56-61 years). We raise in our methods that whilst it is difficult to determine precisely when chimpanzees become ‘old aged’, previous studies use the age of around 40 years, as from this age survivorship begins to decrease more rapidly (see Wood et al., Science 2023). Indeed, one focal individual (Tua) disappeared during the period of our study (presumed dead), and one other individual died in 2017 (Velu), the year after our final sampled field season. As of 2025, two other focal females have since died, and only one focal individual was still alive at Bossou (Jire, the individual exhibiting the least evidence for senescence over our study period). These observations suggest that we successfully captured data from chimpanzees during the oldest ages of their lives for most individuals in the community. Moreover, the period of 1999-2016 contains the majority of data available within the Bossou Archive, with years before and after this window containing comparably less data. This information is included within our results and methods (see sections 2.1 and 4.1).

      For our earliest field season (1999), it is unlikely that senescence had already had an effect on stone-tool use, as we measured efficiency to be high across all efficiency metrics for all individuals. For example, in 1999, the median number of hammer strikes performed by focal chimpanzees ranged from 2-4 strikes, and this was comparable to the efficiency reported across all adults observed in previous studies at Bossou (Biro et al. 2003, Anim. Cog.). This finding suggests that senescence effects had not yet taken place, allowing us to evaluate whether aging affects efficiency over subsequent field seasons. This point is now included in the manuscript on lines 449-452. 

      We sampled at 4-to-5-year intervals to balance the time-intensive nature of fine-scale behavior coding against the need to sample data across the extended 17-year time window available in our study. We limited the final year to 2016 as, in following years, data were collected using different sampling protocols (though, see limited data from 2018 in the supplementary materials). We aimed to keep the intervals between years as consistent as possible (approx. 4 years); however, for some years data were not collected at Bossou, due to disease outbreaks in the region. In these instances, we selected the closest field season where suitable data were available for study (always +/- 1 year). We have provided further clarification surrounding our sampling regime in the methods (see amendments in section 4.1)

      With measuring and interpreting the 'efficiency' of behaviors, there are in-built assumptions about the goals of the agents and how we can define efficiency. First, it may be that efficiency is not an intentional goal for nut-cracking at all, but rather, e.g., productivity as far as the number of uncrushed kernels (cf. Putt 2015). Second, what is 'efficient' for the human observer might not be efficient for the chimpanzee who is performing the behavior. More instances of tool-switching may be considered inefficient, but it might also be a valid strategy for extracting more from the nuts, etc. Understanding the goals of chimpanzees may be a difficult proposition, but these are uncertainties that must be kept in mind when interpreting and discussing 'decline' or any change in technological behaviors over time.

      We agree that knowing precisely how chimpanzees perceive their own efficiency during tool use is unlikely to be available through observation alone. However, under optimal foraging theory, it is reasonable to assume that animals aim to economize foraging behaviors such that they maximize their rate of energy intake. Moreover, a wealth of studies demonstrate that adult chimpanzees acquire and refine tool-using skill efficiency throughout their lives. For example, during nut cracking, adults often select tools with specific properties that aid efficient nut cracking (Braun et al. 2025, J. Hum. Evol.; Carvalho et al. 2008, J. Hum. Evol.; Sirianni et al. 2015, Anim. Behav.); perform nut cracking using more streamlined combinations of actions than less experienced individuals (Howard-Spink et al. 2024, Peer J; Inoue-Nakamura & Matsuzawa 1997, J. Comp. Psychol.), and as a result end up cracking nuts using fewer hammer strikes, indicating a higher level of skill (Biro et al. 2003, Anim. Cogn.; Boesch et al. 2019, Sci. Rep.). Ultimately, these factors suggest that across adulthood, experienced chimpanzees perform nut cracking with a level of efficiency which exceeds novice individuals, including across the whole behavioral sequence for tool use, even if they are not aware or intending to do so. Previous studies at Bossou have also highlighted that there are stable inter-individual differences in efficiency of individuals over time (Berdugo et al. 2024, Nat. Hum. Behav.). This pattern of findings allows us to ask whether this acquired level of skill is stable across the oldest years of an individual’s life, or whether some individuals experience decreased efficiency with age. In addition, our selection of efficiency metrics is in keeping with a wealth of studies which examine the efficiency of stone-tool using in apes, thus, we argue that this is not problematic for our study.

      As we stated in our initial responses to reviewers, it is unlikely that tool switching is a valid strategy for tool use, as it is so rarely performed by proficient adult nut crackers (including earlier in life for our focal individuals). Nevertheless, we did not find a significant change in tool switching for oil-palm nut cracking, and this behavioral change was only observed when Yo was cracking coula nuts. As we have now moved discussion of coula nut cracking to the supplementary materials (and tempered discussion of coula nut cracking to emphasize the need for more data) this behavioral variable does not influence our reported results. 

      In our discussion, we also highlight how seemingly less efficient actions may reflect a valid strategy for nut cracking. E.g. a greater number of tool strikes may reflect a strategy of compensation for progressive tool wear. This would still reflect a reduced efficiency (e.g. in terms of the rate at which kernels can be consumed), but may perhaps borne for the necessity to accommodate for changes in an individuals’ physical affordances with aging. Thus, we do take the Reviewer’s point into account, but by using an alternative, more likely, example given the available data. We have now emphasized this point in lines 521-527.

      We have also clarified these matters by adding more information into our methods (see lines 798-802 and 828-829), highlighting that we take a perspective on efficiency that reflects the speed of nut processing and kernel consumption, and the number of different behavioral elements required to do so. Our phrasing now explicitly avoids using language that assumes that individuals’ have some perception of their own efficiency during tool use.

      For the study of the physiological impact of senescence of tool use (i.e., on strength and coordination), the study would benefit from the inclusion of variables like grip type and (approximate) stone size (Neufuss et al., 2016). The size and shape of stones for nut-cracking have been shown to influence the efficacy and 'efficiency' of tool use (i.e., the same metrics of 'efficiency' implemented by Howard-Spink et al. in the current study), meaning raw material properties are a potential confound that the authors have not evaluated. 

      We did not collect this data as part of our study. Whilst grip type could be a useful variable to measure for future studies, it is not necessary to demonstrate senescence per se. However, we agree that this could be a fruitful avenue to understand changes in behavior at greater granularity, and have added this as a recommendation for further study. We also now provide a discussion on stone dimensions and materials as part of our limitations (see lines 581-589 for both points).

      Similarly, inter- and intraspecific variation in the properties of nuts being processed is another confound (Falótico et al., 2022; Proffitt et al., 2022;). If oil palm nuts were varying year-to-year, for example, this would theoretically have an effect on the behavioral forms and strategies employed by the chimpanzees, and thus, any metric of efficiency being collected and analyzed. Further, it is perplexing that the authors analyze only one year where the coula nuts were provided at the test site, but these were provided during multiple field seasons. It would be more useful to compare data from a similar number of field seasons with both species if we are to study age-related changes in nut processing over time (one season of coula nut-cracking certainly does not achieve this). 

      We have moved all discussion of coula nuts to the supplementary materials so as to avoid any confusion with oil-palm nuts (see comments from Reviewer 2, and our response). Nut hardness may influence the difficulty with which nuts are cracked, with one of the most likely factors influencing nut hardness being its age: young nuts are relatively harder to crack, whereas older nuts, which are often worm-eaten or can be empty, crack more easily, yet are not worth cracking (Sakura & Matsuzawa, 1991; Ethology). We largely controlled for this in our study, as the nuts provided at outdoor laboratories were inspected to ensure that the majority of them were of suitable maturity for cracking, and we now clarify this control in our methods (see lines 678-680) and when discussing our study limitations (see lines 551-558). In these sections, we also highlight a previous study at Bossou that shows chimpanzees select nuts which can be readily cracked, based on their age (Sakura & Matsuzawa, 1991; Ethology).

      We acknowledge that we are limited in the extent to which we can control for interannual variation in ecology with our available data. However, we highlight why interannual variability is unlikely to fully explain our results (see lines 551-580 and response to comments from Reviewer 1). We also highlight in our limitations section that future studies should (where possible) aim to collect more ecological data to account for possible confounds more rigorously.

      Both individual personality (especially neophilia versus neophobia; e.g., Forss & Willems, 2022) and motivation factors (Tennie & Call, 2023) are further confounds that can contribute to a more valid interpretation of the patterns found. To draw any conclusions about age-related changes in diet and food preferences, we would need to have data on the overall food intake/preferences of the individuals and the food availability in the home range. The authors refer briefly to this limitation, but the implications for the interpretation of the data are not sufficiently underlined (e.g., for the relevance of age-related decline in stone tool-use ability for individual survival). 

      In our discussion, we highlight that multiple aging factors may influence apes’  dietary preferences and motivations to attend experimental (and perhaps also naturally-occurring) nut cracking sites (see lines 397-443 and 542-550). We do not believe that neophobia is a likely driver underlying our results, given that the outdoor laboratory has been used to collect data for many decades, including over a decade prior to the first field season in which data were sampled for our study (now highlighted in lines 692-694). In addition, previous studies at Bossou have determined that the outdoor laboratory is visited with comparable frequency to naturallyoccurring nut cracking sites, which makes any form of novelty bias unlikely (this information is now included in our methods, see lines 397-400, and also 687-689). 

      We agree that further information is required about foraging behaviours across the home range to understand changes in attendance at the outdoor laboratory, and have now provided more clarity on this within the limitations section of our discussion 542-550. In our discussion of individual survivability, we state clearly that we cannot make a conclusion about how changes in tool use influence survival with the available data, and assert that this would require data across the home range (see lines 627-638). We agree that future research is needed to assess whether changes in tool use would influence survivability, and also suggest that it may not be survival-relevant; instead changes in tool use with aging may simply be a litmus test for detecting more generalized senescence.

      Generally speaking, there is a lack of consideration for temporal variation in ecological factors. As a control for these, Howard-Spink and colleagues have examined behavioral data for younger individuals from Bossou in the same years, to ostensibly show that patterns in older adults are different from patterns in younger adults, which is fair given the available data. Nonetheless, they seem to focus mostly on the start and end points and not patterns that occur in between. For example, there is a curious drop in attendance rate for all individuals in the 2008 season, the implications of which are not discussed by the authors. 

      As the reviewer points out, when examining the attendance rates of older individuals over sampled field seasons, we used the attendance rates of younger individuals as a control. However, we do not run this analysis using start and end points only. Attendance rates were included in our model across the full range of sample field seasons. However, as the key result here is an interaction term between age cohort (old) and the field season (scaled about the mean), we supplement this significant statistical result with a digestible comparison of attendance rates between the first and last field season, to give a general sense of effect size. We have clarified that all data were used in our model (see line 229, and also the legend for Table 2), and in this section we also provide all key model outputs and signpost where the full model output can be found in the supplementary materials.

      As far as attendance, Howard-Spink and colleagues also discuss how this might be explained by changes in social standing in later life (i.e., chimpanzees move to the fringes of the social network and become less likely to visit gathering sites). This is not senescence in the sense of physiological and cognitive decline with older age. Instead, the reduced attendance due to changes in social standing seems rather to exacerbate signs of aging rather than be an indicator of it itself. The authors also mention a flu-like epidemic that caused the death of 5 individuals; the subsequent population decline and related changes in demography also warrant more discussion and characterization in the manuscript. 

      We have adapted this part of the discussion to make it clear that social aging is not necessarily equivalent to physiological and cognitive aging. We have also clarified in this section the changes in demography at Bossou during our study, which may have further impacted social behaviors (see lines 423-443). 

      Understandably, some of these issues cannot be evaluated or corrected with the presented dataset. Nonetheless, these undermine how certain and/or deterministic their conclusions can really be considered. Howard-Spink et al. have not strongly 'demonstrated' the validity of relationships between the variables of the study. If anything, their cursory observations provide us with methods to apply and hypotheses to test in future studies. It is likely that with higher-resolution datasets, the individual variability in age-related decline in tool-use abilities will be replicated. For now, this can be considered a starting point, which will hopefully inspire future attempts to research these questions. 

      We thank the reviewer for their comments. We have adapted our manuscript to highlight that we agree that it serves a starting point for answering these valuable questions; however, we do feel that we can contribute meaningful evidence that it is likely aging effects underlying the findings in our data (see responses above). We agree with the reviewer that further study is needed to understand these questions in more detail, and have tried to ensure that our conclusions are suitably tempered, and the recommendations for research are heavily encouraged to build on our findings.  

      Falótico, T., Valença, T., Verderane, M. & Fogaça, M. D. Stone tools differences across three capuchin monkey populations: food's physical properties, ecology, and culture. Sci. Rep. 12, 14365 (2022). 

      This has now been cited.

      Forss, S. & Willems, E. The curious case of great ape curiosity and how it is shaped by sociality. Ethology 128, 552-563 (2022). 

      We do not cite this – see above.

      Neufuss, J., Humle, T., Cremaschi, A. & Kivell, T. L. Nut-cracking behaviour in wild-born, rehabilitated bonobos (Pan paniscus): a comprehensive study of hand-preference, hand grips and efficiency. Am. J. Primatol. 79, e22589 (2016). 

      This has now been cited.

      Proffitt, T., Reeves, J. S., Pacome, S. S. & Luncz, L. V. Identifying functional and regional differences in chimpanzee stone tool technology. R. Soc. Open Sci. 9, 220826 (2022). 

      This has now been cited.

      Putt, S. S. The origins of stone tool reduction and the transition to knapping: An experimental approach. J. Archaeol. Sci.: Rep. 2, 51-60 (2015). 

      We do not cite this, as we instead cite studies which highlight chimpanzees’ ability to become more efficient in tool use with repeated practice (see above). 

      Tennie, C. & Call, J. Unmotivated subjects cannot provide interpretable data and tasks with sensitive learning periods require appropriately aged subjects: A Commentary on Koops et al. (2022) "Field experiments find no evidence that chimpanzee nut cracking can be independently innovated". ABC 10, 89-94 (2023). 

      We do not cite this – see above

      Reviewer #2 (Recommendations for the authors):

      Minor Comments: 

      (1) Line 494: Citation #53 is listed twice. 

      This has been amended.

      (2) Line 501: The term 'culturally-dependent' as used here is, at best, controversial, and at worst, misapplied. I would recommend replacing it with simply the term 'cultural'. 

      This has been changed to ‘cultural’.

      Major Comments: 

      For the Introduction, in the paragraph starting on Line 91, and the Discussion, starting on Line 369, I would recommend some simple re-structuring of the argumentation. As many in the Public Review, the changes in social standing according to age are not necessarily a case of senescence in the very sense of physiological or cognitive changes of the individual. This seems to have had an effect on attendance rates, which then could have been a driver of behavioral changes and even cognitive decline as ostensibly measured by the other variables. The social impact of aging should be mentioned in the Introduction (it is not currently) and the social and physiological/cognitive effects of aging should be separated in the Discussion. You can then discuss more clearly how the former via other behavioral changes can accelerate the latter (or not). 

      We take the point raised about social aging. Integrating information about social aging into the introduction was challenging without disrupting the flow of the paper; however, we have included these valuable points in the discussion (see lines 423-443). We now structure this section to clearly distinguish social aging, and discuss how, in tandem with changes in demography at Bossou, it may have influenced rates of attendance to the outdoor laboratory over the years. We do not go into detail about how social aging may interact with physiological or cognitive effects of aging, as we cannot support this with the available data, however we highlight at the end of this paragraph how all of these possible factors require further investigation.

      For the present study, it will either be impossible or impractical to gather data on the yearly ecological conditions, contextualized dietary preferences, individual personalities, etc., so I would not ask that you do so. It is important, however, to temper some of the claims being made in the manuscript about what you have 'determined' about the nature of senescence in chimpanzees and to be more transparent about the limitations and potential confounds when interpreting the data. To avoid repetition, the key points can be found in the Public Review under 'Weaknesses'. 

      We appreciate the reviewer’s understanding of the limitations of our study. Some of these factors – such as individual personalities and dietary preferences – are addressed somewhat by our use of long-term data at the level of the individual, particularly in the analyses of efficiency, where we model individuals’ behaviors compared to those in earlier years offers an individuallybespoke control. However, there are other ecological variables of possible importance that we cannot evaluate. We now address several of these points raised by reviewers in the discussion, to ensure transparency of reporting (see limitations section of our discussion, and results to the comments provided by Reviewer 1, and our responses to points raised in the Public Review). We have also tempered some of the phrasing surrounding our conclusions, where we say that this is the first evidence that aging can impact chimpanzee tool use, we also highlight the need for an assortment of further studies. 

      Finally, the integration of the coula nut-cracking data is not well-executed as it stands. I would recommend that they collect and analyze equivalent behavioral data from the other years where coula nuts were provided. By examining only one season of coula nut-cracking, we cannot contextualize the data to past seasons; there is no sense in comparing one season of coula nut-cracking (i.e., in a sense of efficiency) to roughly contemporary seasons of palm-nut cracking due to, as you describe, differences in physical properties of the nuts. If you are not able to collect the additional data and carry out the requisite analysis, then I would recommend that the coula nut-related sections be removed from the manuscript, so that it does not detract from the logical flow of arguments and distract from the other data, which is more logically-attuned to your research questions. 

      We have removed this from the main manuscript. We have decided to include the information surrounding coula nut cracking in the supplementary materials, as this information is still relevant to the findings of our study, and may interest some readers. However, we have phrased this information to make it clear that further data is needed to compare coula nut cracking across years.

      These criticisms do not subtract from the (potential) value or importance of the work for the field. This is, of course, an important contribution to an understudied topic. As such, I would gladly advocate for the manuscript, assuming the authors would reflect on the listed caveats and make changes in response to the 'Major Comments'. 

      We thank the reviewer for their comments.

    1. Author response:

      The following is the authors’ response to the original reviews

      Reviewer 1 (Public reviews):

      (1) Commander-Independent Role of COMMD3: While the authors provided evidence to support the Commander-independent role of COMMD3-such as the absence of other Commander subunits in the CRISPR screen and not decreased COMMD3 levels in other subunit-KO cells- direct evidence is lacking. The mutation that specifically disrupts the COMMD3-ARF1 interaction could serve as a valuable tool to directly address this question.

      The Reviewer raised an excellent point. We fully agree with the Reviewer that multiple lines of evidence are needed to support the novel Commander-independent function of COMMD3.

      Comparative genetic analyses in Figures 4 and 5 indicate that COMMD3 regulates endosomal retrieval independently of the Commander complex. In Figure 8 of the revised manuscript, we show that point mutations introduced into the COMMD3:ARF1 interface impair this Commander-independent function. Moreover, Figure 6 demonstrates that ARF1 upregulation fully rescues the KO phenotype of COMMD3. In addition, Figure S2 further supports that COMMD3 levels, but not those of other Commander subunits, correspond to its Commander-independent function in endosomal trafficking. We have also revised the Discussion section to elaborate on the implications of these findings. We appreciate the Reviewer’s advice.

      (2) Role of ARF1 in Cargo Selection: The Commander-independent function of COMMD3 appears cargo-dependent and relies on ARF1's role in cargo selection. The authors should investigate whether KO/KD of ARF1 reduces cell surface levels of ITGA6 and TfR.

      The Reviewer correctly pointed out that KO/KD of ARF1 may provide further insights into the Commander-independent function of COMMD3. However, since ARF1 is involved in cargo sorting at both the endosome and the trans-Golgi network, its KO would disrupt multiple trafficking routes, making the data difficult to interpret. Instead, we focused on point mutations in the NTD that specifically disrupt ARF1 binding without affecting the function of the Commander complex (Fig. 8). As these mutations impair the Commander-independent function of COMMD3, our data strongly support a direct role for ARF1 in this recycling pathway. We note that the discovery of a novel trafficking pathway inevitably opens many research directions. One such direction is to systematically identify cargoes that rely on COMMD3 but not the Commander complex for endosomal retrieval.

      (3) Impact on TfR Stability: Figure 7D suggests that TfR protein levels are reduced in COMMD3-KO cells, potentially due to degradation caused by disrupted recycling. This raises the question of whether the observed reduction in cell surface TfR is due to impaired endosomal recycling or decreased total protein levels. The authors should quantify the ratio of cell surface protein to total protein for TfR, GLUT-SPR, and ITGA6 in COMMD3-KO cells.

      Based on the Reviewer's suggestion, we quantified both the total levels and the surface-tototal ratio of TfR, as shown in Figure S1 of the revised manuscript. These new data further support the conclusion that defects in TfR retrieval lead to its lysosomal degradation. The GLUT-SPR data presented in the main figures represent the surface-to-total ratio of the GLUT-SPR reporter. We thank the Reviewer for the important suggestion.

      Reviewer #1 (Recommendations for the authors):

      (1) Commander-Independent Role of COMMD3: The mutation that specifically disrupts the COMMD3-ARF1 interaction could serve as a valuable tool to directly address this question. The authors should evaluate whether the full-length mutant of COMMD3 can rescue decreased levels of CCDC93 and VPS35L, as well as cell surface ITGA6, TfR, and GLUT4 inCOMMD3-KO cells.

      This is an excellent point. In our mechanistic experiments, we focused on the NTD of COMMD3 because this domain mediates its Commander-independent function and is not involved in forming the Commander holo-complex. This approach allowed us to draw unambiguous conclusions. Nevertheless, we anticipate that full-length COMMD3 carrying these point mutations would also be defective in regulating Commander-independent cargo.

      (2) Role of ARF1 in Cargo Selection: The authors should investigate whether KO/KD of ARF1 reduces cell surface levels of ITGA6 and TfR. Was ARF1 identified in the initial CRISPR screen? If so, this should be explicitly noted. Alternatively, does ARF1 overexpression rescue ITGA6 levels in COMMD3-KO cells? Furthermore, does ARF1 overexpression rescue TfR levels in COMMD3 and CCDC93 double-KO cells?

      Reinto the Commander-independent function of COMMD3. However, since ARF1 is involved in cargo sorting at both the endosome and the trans-Golgi network, its KO would disrupt multiple trafficking routes, making the data difficult to interpret. Instead, we focused on point mutations that specifically disrupt ARF1 binding without affecting the function of the Commander complex (Fig. 8). Since these mutations impair the Commander-independent function of COMMD3, our data strongly support a direct role for ARF1 in this novel recycling pathway. Based on our genetic data, we anticipate that all COMMD3-dependent cargoes will be similarly rescued in ARF1-overexpressing cells. In line with the Reviewer's comment, a key research direction we are currently pursuing is systematically determining how surface protein levels are affected by COMMD3 KO and ARF1 overexpression using surface proteomics.

      (3) Inconsistency in COMMD3 Rescue Levels (Figure 5A): Figure 5A shows comparable or higher levels of COMMD3 in rescued cells than in CCDC93-KO and VPS35L-KO cells. However, COMMD3 rescue did not increase cell surface TfR as much as in CCDC93-KO and VPS35L-KO cells. This inconsistency should be discussed or validated.

      To address the Reviewer’s inquiry, we quantified COMMD3 expression levels in these cell lines using multiple independent experiments. The new data are presented in Figure S2 of the revised manuscript. These expanded datasets allowed us to more accurately determine the relationship between COMMD3 expression and our genetic data. Since the Commander complex remains intact in the COMMD3 rescue cells, a significant portion of COMMD3 proteins are expected to be incorporated into the Commander complex, which does not regulate TfR recycling. In contrast, because the Commander complex is disrupted in Ccdc93 and Vps35l KO cells, all COMMD3 proteins are available to regulate TfR recycling in a Commander-independent manner. These findings are fully consistent with the similar surface TfR levels observed in Ccdc93/Vps35l KO cells and COMMD3 overexpressing cells. We thank the Reviewer for this excellent suggestion.

      (4) Significance of NTD in COMMD3 Function: The conclusion that "the NTD of COMMD3 mediates its Commander-independent function and interacts with ARF1" (Page 12) is not fully supported without a side-by-side comparison of NTD, CTD, and FL COMMD3 in the same experiment (e.g., Figures 6B and 6G). Additional data is needed to strengthen this claim.

      We conducted the experiment suggested by the Reviewer and included the data in Figure S3. Our results indicate that the COMMD3 CTD cannot mediate the Commander-independent function of COMMD3 in endosomal retrieval. We appreciate the Reviewer’s suggestion.

      (5) ARF1 Stabilization Experiments: To substantiate the claim that COMMD3 binds and stabilizes the GTP-form of ARF1, the authors should include a comparative experiment showing GTP-form, GDPform, and wild-type ARF1 (e.g., Figures 6G and 7C).

      We fully agree with the Reviewer that it would be important to compare how the ARF1:COMMD3 interaction is influenced by the nucleotide-binding state. However, trapping ARF1 in its GDP-bound state remains unfeasible, and nucleotide-free small GTPases are inherently unstable. In addition, WT ARF1 likely exists as a mixture of GTP- and GDP-bound forms, further complicating the analysis. To address the Reviewer’s comment, we used AlphaFold3 predictions. Interestingly, we found that the ipTM score of GTP-ARF1:COMMD3 is significantly higher than that of GDP-ARF1:COMMD3 or apo-ARF1:COMMD3, supporting our conclusion that COMMD3 recognizes and stabilizes the active form of ARF1.

      (6) Validation of NTD Mutation (Figure 8): Co-immunoprecipitation or cellular co-localization experiments should be performed to confirm that the NTD mutation disrupts the interaction between COMMD3 and ARF1, as depicted in Figure 8.

      This is an important question, and the best approach to address it would be to measure the binding affinity of the WT and mutant proteins using ITC or SPR. However, this is currently unfeasible, as we have not yet obtained pure recombinant COMMD3 and GTP-ARF1 proteins. Co-IP, by nature, is a crude assay that often fails to detect changes in binding affinity. A previous study on other proteins showed that mutations in protein-binding interfaces strongly reduced binding affinity as measured by SPR, but these changes would have been missed by co-IP assays (PMID: 25500532). In agreement with this limitation, our co-IP experiments did not yield conclusive results. Instead, we focused on structure-guided genetic experiments, which unequivocally demonstrated the effects of targeted mutations on the Commander-independent function of COMMD3. 

      Reviewer #2 (Public review):

      (1) All existing data suggest that COMMD3 is a subunit of the Commander complex. Is there any evidence that COMMD3 can exist as a monomer?

      The Reviewer raised an intriguing point. Indeed, COMMD proteins, including COMMD3, can exist outside the Commander holo-complex and form homo- or hetero-oligomers, as monomeric COMMD proteins are likely unstable. These observations align well with the Commander-independent function identified in this study. We have revised the Discussion section of the manuscript to further elaborate on this point and thank the Reviewer for the suggestion.

      (2) In Figure 9, the author emphasizes COMMD3-dependent cargo and Commander-dependent cargo. Can the authors speculate what distinguishes these two types of cargo? Do they contain sequence-specific motifs?

      This is another important question. Our data clearly demonstrate that COMMD3 has a Commander-independent function in addition to its canonical role within the Commander holocomplex. Since cargo proteins typically possess multiple sorting signals that operate at different stages of the exocytic and endocytic pathways, identifying COMMD3-dependent sorting signals remains a challenge. ARF4 has been shown to specifically recognize the VXPX motif (PMID: 15728366), suggesting that ARF1 may similarly bind cytosolic sorting signals, with COMMD3 stabilizing this interaction. A key future direction is to systematically identify COMMD3-dependent cargo proteins and elucidate the mechanisms underlying their endosomal sorting. We have revised the Discussion section of the manuscript to explicitly address this point and thank the Reviewer for this important suggestion.

      (3) What could be the possible mechanism underlying the observation that the knockout of COMMD3 results in larger early endosomes? How is the disruption of cargo retrieval related to the increase in endosome size?

      The endosomal retrieval process is critical for recycling membrane proteins and lipids back to the plasma membrane or the trans-Golgi network. When this process is disrupted, cargo that should be recycled accumulates within endosomes, leading to their enlargement. For example, defects in retromer function can cause endosomal swelling due to cargo accumulation (PMID: 33380435). We added this citation to the revised manuscript and thank the Reviewer for the advice. 

      Reviewer 3 (Recommendations for the authors):

      (1) Figure 4: How do the authors define Commander-dependent vs. Commander-independent cargos?

      In Figure 4, the surface expression of ITGA6 is reduced to approximately 0.75 across all knockouts. However, there is a similar level of reduction for GLUT4-SPR in the commd5 knockout and for LAMP1 in the commd5 and commd1 knockouts. Are GLUT4-SPR and LAMP1 Commander-dependent or Commander-independent cargos? Additionally, how does COMMD3 specifically identify/distinguish these cargos?

      This is an excellent point. Our data suggest that TfR is a COMMD3-dependent but Commander-independent cargo, whereas ITGA6 is a Commander-dependent cargo that does not involve COMMD3-specific functions. The other two cargoes we examined—GLUT-SPR and LAMP1—primarily rely on COMMD3, with the Commander complex playing a minor role. Together, these observations clearly demonstrate that COMMD3 has a Commander-independent function in addition to its canonical role within the Commander holo-complex. Since cargo proteins typically possess multiple sorting signals that operate at different stages of the exocytic and endocytic pathways, identifying COMMD3-dependent sorting signals remains a challenge. ARF4 has been shown to specifically recognize the VXPX motif (PMID: 15728366), suggesting that ARF1 may similarly bind cytosolic sorting signals, with COMMD3 stabilizing this interaction. A key future direction is to systematically identify COMMD3-dependent cargo proteins and elucidate the mechanisms underlying their endosomal sorting. We have revised the Discussion section of the manuscript to explicitly address this point. We thank the Reviewer for this important suggestion.

      (2) There is an increase in the surface expression of GLUT4-SPR in the commd1 knockout. Is this increase significant? The figure suggests a significant increase, but the text states it remains unchanged. Clarification is needed.

      We found that surface levels of GLUT-SPR were slightly increased in Commd1 KO cells, in stark contrast to the strong reduction observed in Commd3 KO cells (Fig. 4B). This finding is consistent with our conclusion that COMMD3 has a distinct role from other Commander subunits. We have revised the Results section to more clearly describe these data and thank the Reviewer for the advice.

      (3) Figure 5A: To support the claim that COMMD3 is upregulated in the vps35l KO/Ccdc93 KO, the authors should quantify COMMD3 expression. Also, why is there a Vps35l band present in the Vps35l knockout cells?

      Based on the Reviewer’s suggestion, we quantified the total levels of COMMD3 and included these new data in Figure S2. In this study, gene deletion was achieved through the simultaneous introduction of two independent gRNAs. Based on our previous experience, this strategy typically results in the complete loss of gene expression. We posit that the residual band observed in Vps35l KO cells originates from background signals, such as nonspecific staining by the antibody.

      (4) Figure 7: It is intriguing that COMMD3 stabilizes Arf1-GTP and can compensate for COMMD3 in knockout cells. However, is this stabilization specific to TfR cargo only? The authors should test additional Commander-dependent and Commander-independent cargos to clarify this point.

      Based on our genetic data, we anticipate that all COMMD3-dependent cargoes will be similarly rescued in ARF1-overexpressing cells. In line with the Reviewer's comment, an important direction we are pursuing is the use of surface proteomics to systematically determine how surface protein levels are affected by COMMD3 KO and ARF1 overexpression.

      (5) Is Arf1 interaction specific to COMMD3? The authors should investigate the effects of Arf1 knockout on COMMD3 expression and test its role in regulating Commander-dependent and Commander-independent cargos.

      The Reviewer raised an excellent point. Since ARF1 is involved in cargo sorting at both the endosome and the trans-Golgi network, its KO would interfere with multiple trafficking routes and the data would be difficult to interpret. Thus, in this work, we focused on the function and mechanism of the COMMD3:ARF1 complex on the endosome. Based on the suggestion of the Reviewer, we used AlphaFold3 to predict ARF1 binding to COMMD proteins. Interestingly, the complex with the highest predicted ipTM score is COMMD3:ARF1, while other COMMD proteins have much lower predicted binding scores. These results are consistent with the results of our unbiased CRISPR screens and targeted gene KO, and further support the conclusion that the COMMD3:ARF1 binding is specific and physiologically important in endosomal trafficking.

    1. Author response:

      The following is the authors’ response to the original reviews

      Reviewer #1 (Public review):

      Weaknesses:

      (1) The selection of inactivated conformations based on AlphaFold modeling seems a bit biased. The authors base their selection of the “most likely” inactivated conformation on the expected flipping of V625 and the constriction at G626 carbonyls. This follows a bit of the “Streetlight effect”. It would be better to have selection criteria that are independent of what they expect to find for the inactivated state conformations. Using cues that favour sampling/modeling of the inactivated conformation, such as the deactivated conformation of the VSD used in the modeling of the closed state, would be more convincing. There may be other conformations that are more accurately representing the inactivated state. I see no objective criteria that justify the non-consideration of conformations from cluster 3 of the inactivated state modeling. I am not sure whether pLDDT is a good selection criterion. It reports on structural confidence, but that may not relate to functional relevance.

      We sincerely thank the reviewer for their perceptive critique highlighting potential bias in selecting the inactivated conformation. We recognize that over-relying on preconceived traits could limit exploration of diverse inactivated states, and we appreciate the opportunity to address this concern.

      Although we selected the model with the flipped V625 in the selectivity filter (SF) from the first round of inactivated-state sampling as the template for the second round, the resulting models still exhibited substantial diversity in their SF conformations. This selection primarily served to steer predictions away from the open-state configuration observed in the PDB 5VA2 SF, and we have clarified this rationale in the Methodology section. To assess conformational variability, we examined backbone dihedral angles (phi φ and psi ψ) at key residues in the selectivity filter (S624 – G628) and drugbinding region on the pore-lining S6 segment (Y652, F656), of all 100 models sampled in the subsequent inactivatedstate-sampling attempt. By overlaying the φ and ψ dihedral angles from different models, including the open state (PDB 5VA2-based), the closed state, and representative models from AlphaFold inactivated-state-sampling Cluster 2 and Cluster 3, we found that these conformations consistently fall within or near high-probability regions of the dihedral angle distributions. This indicates that these structural states are well represented within the ensemble of conformations sampled by AlphaFold within the scope of this study, particularly at functionally critical positions.

      Following the analysis above and consistent with the reviewer’s suggestion, we evaluated the top representative model from inactivated-state-sampling Cluster 3 (named “AF ic3”), which we had initially excluded. This model demonstrated SF residue G626 carbonyl oxygen flipped away from the conduction pathway, hinting at potential impact on ion conduction, yet its pore region structurally resembled the open state (Figure S9a, b). To test this objectively, we ran molecular dynamics (MD) simulations (2 runs, 1 μs long each, with applied 750 mV voltage) with varied initial ion/water configurations in the SF, finding it consistently open and conducting throughout (Figure S9c, d), consistent with our previous observations in Figure S11 that ion conduction can still occur when the upper SF is dilated. Drug docking (Figure S12) further revealed that the model exhibited binding affinities similar to those for the PDB 5VA2-based openstate structure. These findings combined led us to classify it as a possible alternative open-state conformation.

      Models from Cluster 4 were not tested due to extensive steric clashes, where residues in the SF overlapped with neighboring residues from adjacent subunits. The remaining models displayed SF conformations that combined features from earlier clusters. However, due to subunit-to-subunit variability, where individual subunits adopted differing conformations, they were classified as outliers. This combination of features may be valuable to investigate further in a follow-up study.

      We acknowledge that our approach is just one of many ways to sample different states, and alternative strategies, such as generating more models, varying multiple sequence alignment (MSA) subsampling, or testing different templates, might reveal improved models. Given that hERG channel inactivation likely spans a spectrum of conformations, our resource limitations may have restricted us to exploring and validating only part of this diversity. Nevertheless, the putative inactivated (AlphaFold Cluster 2) model’s non-conductivity and improved affinity for drugs targeting the inactivated state observed in our study suggests that this approach may be capturing relevant features of the inactivated-state conformation. We look forward to investigating deeper other possibilities in a future study and are grateful for the reviewer’s feedback.

      (2) The comparison of predicted and experimentally measured binding affinities lacks an appropriate control. Using binding data from open-state conformations only is not the best control. A much better control is the use of alternative structures predicted by AlphaFold for each state (e.g. from the outlier clusters or not considered clusters) in the docking and energy calculations. Using these docking results in the calculations would reveal whether the initially selected conformations (e.g. from cluster 2 for the inactivated state) are truly doing a better job in predicting binding affinities. Such a control would strengthen the overall findings significantly.

      We appreciate the reviewer’s insightful suggestion. To address this, we extended our analysis by incorporating an alternative AlphaFold2-predicted model from inactivated-state-sampling cluster 3 as a structural control. This model was established in a previously discussed analysis to be open and conducting as a follow up to comment #1, so we will call it Open (AF ic3) to differentiate it from Open (PDB 5VA2). We evaluated this new model in single-state and multi-state contexts alongside our original open-state model based on the experimental PDB 5VA2 structure. Additionally, we expanded the drug docking procedure to explore a broader region around the putative drug binding site by increasing the sampling space, and we adopted an improved approach for selecting representative docking poses to better capture relevant binding modes.

      Shown in Figure 7 are comparisons of experimental drug potencies with the binding affinities from the molecular docking calculations under the following conditions:

      (a) Single-state docking using the experimentally derived open-state structure (PDB 5VA2)

      (b) Multi-state docking incorporating open (PDB 5VA2), inactivated, and closed-state conformations weighted by experimentally observed state distributions

      (c) Single-state docking using an alternative AlphaFold-predicted open-state (inactivated-state-sampling cluster 3, AF ic3)

      (d) Multi-state docking combining the AlphaFold-predicted open-state (inactivated-state-sampling cluster 3, AF ic3)

      Using only the open-state model (PDB 5VA2) yielded a moderate correlation with experimental data (R<sup>2</sup> = 0.43, r = 0.66, Figure 7a). Incorporating multi-state binding (weighted by their experimental distributions) improved the correlation substantially (R<sup>2</sup> = 0.63, r = 0.79, Figure 7b), boosting predictive power by 47% and underscoring the value of multi-state modeling. Importantly, this improvement was achieved without considering potential drug-induced allosteric effects on the hERG channel conformation and gating, which will be addressed in future work.

      Next, we substituted the PDB 5VA2-based open-state model with the AF ic3 open-state model. Docking to this alternative model alone produced similar performance (R<sup>2</sup> = 0.44, r = 0.66, Figure 7c), and incorporating it into the multi-state ensemble further improved the correlation with experiments (R<sup>2</sup> = 0.64, r = 0.80, Figure 7d), representing a 45% gain in R<sup>2</sup> and matching the performance of multi-state docking results based on the PDB 5VA2-derived model.

      These findings suggest that the predictive power of computational drug docking is enhanced not merely by the accuracy of individual models, but by the structural diversity and complementarity provided by an ensemble of protein conformations. Rather than relying solely on a single experimentally determined protein structure, the ensemble benefits from incorporating AlphaFold-predicted models that capture alternative conformations identified through our state-specific sampling approach. These diverse protein models reflect different structural features, which together offer a more comprehensive representation of the ion channel’s binding landscape and enhance the predictive performance of computational drug docking. Overall, these results reinforce that multi-state modeling offers a more realistic and predictive framework for understanding drug – ion channel interactions than traditional single-state approaches, emphasizing the value of both individual model evaluation and their collective integration. We are grateful for the reviewer’s suggestion.

      (3) Figures where multiple datapoints are compared across states generally lack assessment of the statistical significance of observed trends (e.g. Figure 3d).

      We appreciate the reviewer’s comment on the statistical significance assessment in Figure 3d. To clarify, the comparisons shown in the subpanels are based on three selected representative models for each state, rather than a broader population sample (similarly for Figure 3b). In the closed-state predicted models, the strong convergence of the voltagesensing domain (VSD), with an all-atom RMSD of 0.36 Å between cluster 1 and 2 closed-state sampling models and 0.95 Å to the outlier cluster, indicates minimal structural variation. Those RMSD values shown in the manuscript text demonstrates good convergence and by themselves represent statistical significance assessment of those models. This trend extends to open-state and inactivated-state AlphaFold models with similarly limited differences in the VSD regions among them. This convergence suggests that population-based statistical analysis may not reveal meaningful deviations, as the low variability among models limits the insights beyond those obtained from comparing representative structures.

      Nonetheless, we acknowledge this limitation. In future studies, we plan to explore alternative modeling approaches to introduce greater variability, enabling a more robust statistical evaluation of state-specific trends in the predictions.

      (4) Figure 3 and Figures S1-S4 compare structural differences between states. However, these differences are inferred from the initial models. The collection of conformations generated via the MD runs allow for much more robust comparisons of structural differences.

      We have explored these conformational state dynamics through MD simulations for the Open (5VA2-based), Inactivated (AlphaFold Cluster 2), and Closed-state models, as presented in Figures S7, S8, S10, S11. These figures provide detailed insights: Figure S7-S8 analyzes SF and pore conformation dynamics, including averaged pore radii with and without voltage and superimposed conformational ensembles; Figure S10 tracks cross-subunit distances between protein backbone carbonyl oxygens, revealing sequential SF dilation steps near residues F627 an G628; and Figure S11 illustrates this SF dilation process over time, highlighting residue F627 carbonyl flipping and SF expansion. We appreciate the opportunity to clarify our approach.

      Reviewer #2 (Recommendations for the authors):

      Major concerns:

      (1) Protein fragments are used to model the closed and inactivated states of hERG, but the choices of fragments are not well justified. For instance, in Figure 1a, helices from 8EP1 (deactivated voltage-sensing domain) and a helix+loop from 5VA2 (selectivity filter) are used. Why just the selectivity filter and not the cytosolic domain, for instance? Why not some parts of the helices attached to the selectivity filter, or the whole membrane inserted domain of 8EP1? Same for the inactivated conformation in Figure 1c: why the cytosolic domain only?

      We thank the reviewer for their thoughtful questions regarding our choice of protein fragments for modeling the closed and inactivated states of hERG in Figures 1a and 1c, and we appreciate the opportunity to justify these selections more clearly. Our approach to template selection was guided by our experience that providing AlphaFold2 with larger templates often leads it to overly constrain predictions to the input structure, reducing its flexibility to explore alternative conformations. In contrast, smaller, targeted fragments increase the likelihood that AlphaFold2 will incorporate the desired structural features while predicting the rest of the protein. We have provided a more detailed discussion of this in the methodology section.

      For the closed state (Figure 1a), we chose the deactivated voltage-sensing domain (VSD) from the rat EAG channel (PDB 8EP1) to inspire AlphaFold2 to predict a similarly deactivated VSD conformation characteristic of hERG channel closure, as this domain’s downward shift is a hallmark of potassium channel closure. We paired this with the selectivity filter (SF) and adjacent residues from the open-state hERG structure (PDB 5VA2) to maintain its conductive conformation, as it is generally understood that K<sup>+</sup> channel closure primarily involves the intracellular gate rather than significant SF distortion. Including additional helices (e.g., S5–S6) or the entire membrane domain from PDB 8EP1 risked biasing the model toward the EAG channel’s pore structure, which differs from hERG’s, while omitting the cytosolic domain ensured focus on the VSD-driven closure without over-constraining cytoplasmic domain interactions.

      For the inactivated state (Figure 1c), we initially used only the cytosolic domain from PDB 5VA2 to anchor the prediction while allowing AlphaFold2 to freely sample transmembrane domain conformations, particularly the SF, where the inactivation occurs via its distortion. Excluding the SF or attached helices at this stage avoided locking the model into the open-state SF, and the cytosolic domain alone provided a minimal scaffold to maintain hERG’s intracellular architecture without dictating pore dynamics. Following the initial prediction, we initiated more extensive sampling by using one of the predicted SFs that differs from the open-state SF (PDB 5VA2) as a structural seed, aiming to guide predictions away from the open-state configuration. The VSD and cytosolic domain were also included in this state to discourage pore closure during prediction. Using larger fragments, like the full membrane-spanning domains or additional cytosolic regions from the open-state structure might reduce AlphaFold2’s ability to deviate from the open-state conformation, undermining our goal of capturing more diverse, state-specific features.

      It is worth noting that multiple strategies could potentially achieve the predicted models in our study, and here we only present examples of the paths we took and validated. It is likely that many of the steps may be unnecessary and could be skipped, and future work building on our approach can further explore and streamline this process. A consistent theme underlies our choices: for the closed state, we know the VSD should adopt a deactivated (“down”) conformation, so we provide AlphaFold2 with a specific fragment to guide this outcome; for the inactivated state, we recognize that the SF must change to a non-conductive conformation, so we grant AlphaFold2 flexibility to explore diverse conformations by minimizing initial constraints on the transmembrane region.

      With greater sampling and computational resources, it is possible we could identify additional plausible, non-conductive conformations that might better represent an inactivated state, as hERG inactivation may encompass a spectrum of states. In this study, due to resource limitations, we focused on generating and validating a subset of conformations. Still, we acknowledge that broader exploration could further refine these models, which could be pursued in future studies. We updated the Methods and Discussion sections to reflect this perspective, and we are grateful for the reviewer’s input, which encourages us to clarify our rationale and highlight the adaptability of our approach.

      To demonstrate the broader feasibility of this approach, we applied it to another ion channel system, voltage-gated sodium channel Na<sub>V</sub> 1.5, as illustrated in Figure S14. In this example, a deactivated VSD II from the cryo-EM structure of a homologous ion channel Na<sub>V</sub>1.7 (PDB 6N4R) (DOI: 10.1016/j.cell.2018.12.018), which was trapped in a deactivated state by a bound toxin, was used as a structural template. This guided AlphaFold to generate a Na<sub>V</sub>1.5 model in which all four voltage sensor domains (VSD I–IV) exhibit S4 helices in varying degrees of deactivation. Compared to the cryo-EM openstate Na<sub>V</sub>1.5 structure (PDB 6LQA) (DOI: 10.1002/anie.202102196), the predicted model displays a visibly narrower pore, representing a plausible closed state. This example underscores the versatility of our strategy in modeling alternative conformational states across diverse ion channels.

      (2) While the authors rely on AF2 (ColabFold) for the closed and inactivated states, they use Rosetta to model loops of the open state. Why not just supply 5VA2 as a template to ColabFold and rebuild the loops that way? Without clear explanations, these sorts of choices give the impression that the authors were looking for specific answers that they knew from their extensive knowledge of the hERG system. While the modeling done in this paper is very nice, its generalizability is not obvious.

      We appreciate the reviewer’s question about our use of Rosetta to model loops in the open-state hERG channel (PDB

      5VA2) rather than rebuilding it entirely with ColabFold. In the study, we conducted a control experiment supplying parts of PDB 5VA2 to ColabFold to rebuild the loops, generating 100 models (Figure 2a: predicted open state). The top-ranked model (by pLDDT) differed from our Rosetta-modelled structure by only 0.5 Å RMSD, primarily due to the flexible extracellular loops as expected, with the pore and selectivity filter (our areas of focus) remaining nearly identical. We chose the Rosetta-refined cryo-EM structure as this structure and approach have been widely used as an open-state reference in our other hERG channel studies, such as by Miranda et al. (DOI: 10.1073/pnas.1909196117) and Yang et al. (DOI: 10.1161/CIRCRESAHA.119.316404), to ensure that our results are more directly comparable to prior work in the field. Nonetheless, as both models (with loops modeled by Rosetta or AlphaFold) were virtually identical, we would expect no significant differences if either were used to represent the open state in our study. We have incorporated this clarification into the main text.

      (3) pLDDT scores were used as a measure of reliable and accurate predictions, but plDDT is not always reliable for selecting new/alternative conformations (see https://doi.org/10.1038/s41467-024-515072 and https://www.nature.com/articles/s41467-024-51801-z).

      We acknowledge that while pLDDT is a valuable indicator of structural confidence in AlphaFold2 predictions, its limitations warrant consideration. In our revision, we mitigated this by not relying solely on pLDDT, but we also performed protein backbone dihedral angle analysis of the protein regions of focus in all predicted models to ensure comprehensive coverage of conformational variations. From our AlphaFold modeling results, we tested a model from cluster 3 of the inactivated-state sampling process, which exhibited lower pLDDT scores, and included these results in our revised analysis. We included a note in the revised manuscript’s Discussion section: “As noted in recent studies, pLDDT scores are not reliable indicators for selecting alternative conformations (DOI: 10.1038/s41467-024-51507-2 and DOI: 10.1038/s41467-024-51801-z). To address this, we performed a protein backbone dihedral angle analysis in the regions of interest to ensure that our evaluation captured a representative range of sampled conformations.”

      (4) Extensive work has been done using AF2 to model alternative protein conformations (https://www.biorxiv.org/content/10.1101/2024.05.28.596195v1.abstract, along with some references the authors cite, such as work by McHaourab); another group recently modeled the ion channel GLIC (https://www.biorxiv.org/content/10.1101/2024.09.05.611464v1.abstract). Therefore, this work, though generally solid and thorough, seems more like a variation on a theme than a groundbreaking new methodology, especially because of the generalizability issues mentioned above.

      We sincerely thank the reviewer for acknowledging the solidity of our study and for drawing our attention to the impressive recent efforts using AlphaFold2 to explore alternative protein conformations. These studies are valuable contributions that highlight the versatility of AlphaFold2, and we are grateful for their context in evaluating our work.

      Building on these efforts, our approach not only enhances the prediction of conformational diversity but also introduces a twist by incorporating structural templates to guide AlphaFold2 toward specific functional protein states. More significantly, our study advances beyond mere structural modeling by integrating these conformations with their rigorous validation by incorporating multiple simulation results tested against experimental data to reveal that AlphaFold-predicted conformations can align with distinct physiological ion channel states. A key finding is that drug binding predictions using AlphaFold-derived hERG channel states substantially improve correlation with experimental data, which is a longstanding challenge in computational screening of multi-state proteins like the hERG channel, for which previous structural models have been mostly limited to the open state based on the cryo-EM structures. Our approach not only captures this critical state dependence but also reveals potential molecular determinants underlying enhanced drug binding during hERG channel inactivation, a phenomenon observed experimentally but poorly understood. These insights advance drug safety assessment by improving predictive screening for hERG-related cardiotoxicity, a major cause of drug attrition and withdrawal.

      We view our methodology as a natural evolution of the advancements cited by the reviewer, offering an approach that predicts diverse hERG channel conformational states and links them to meaningful functional and pharmacological outcomes. To address the reviewer’s concern about generalizability, we have expanded the methodology section to make it easier to follow and include additional details. As an example, we show how our approach can be applied to model another ion channel system, Na<sub>V</sub>1.5, in Figure S14.

      Furthermore, to enhance the applicability of our methodology, we have uploaded the scripts for analyzing AlphaFoldpredicted models to GitHub (https://github.com/k-ngo/AlphaFold_Analysis), ensuring they are adaptable for a wide range of scenarios with extensive documentation. This enables users, even those not focused on ion channels, to effectively apply our tools to analyze AlphaFold predictions for their own projects and produce publication-ready figures.

      While it is likely that multiple modeling approaches could lead AlphaFold to model alternative protein conformations, the key challenge lies in validating the physiological relevance of those predicted states. This study is intended to support other researchers in applying our template-guided approach to different protein systems, and more importantly, in rigorously in silico testing and validation of the biological significance of the conformation-specific structural models they generate.

      Minor concerns:

      (1) The authors mention in the Introduction section that capturing conformational states, especially for membrane proteins that may be significant as drug targets, is crucial. It would be helpful to relate their work to the NMR studies domains of the hERG channel, particularly the N-terminal “eag” domain, which is crucial for channel function and can provide insights into conformational changes associated with different channel states (https://doi.org/10.1016/j.bbrc.2010.10.132 ).

      We appreciate the reviewer’s insightful comment regarding the PAS domain and the potential influence of other regions, such as the N-linker and distal C-region, on drug binding and state transitions.

      The PAS domain did appear in the starting templates used for initial structural modeling (as shown in Figure 1a, b, c), but it was not included in the final models used for subsequent analyses. The omission was primarily due to hardwareimposed constraints, as including these additional regions would exceed the memory capacity of our current graphics processing unit (GPU) card, leading to failures during the prediction step.

      The PAS domain, even if not serving as a conventional direct drug-binding site, can influence the gating kinetics of hERG channels. By altering the probability and duration with which channels occupy specific states, it can indirectly affect how well drugs bind. For example, if the presence of the PAS domain shifts hERG channel gating so that more channels enter (and remain in) the inactivated state as was shown previously (e.g., DOI: 10.1085/jgp.201210870), drugs with a higher affinity for that state would appear to bind more potently, as observed in previous electrophysiological experiments (e.g., DOI: 10.1111/j.1476-5381.2011.01378.x). It is also plausible that the PAS domain could exert allosteric effects that alter the conformational landscape of the hERG channel during gating transitions, potentially impacting drug accessibility or binding stability. This is an intriguing hypothesis and an important avenue for future research.

      With access to more powerful computational resources, it would be valuable to explore the full-length hERG channel, including the PAS domain and associated regions, to assess their potential contributions to drug binding and gating dynamics. We incorporated a discussion of these points into the main text, acknowledging the limitations of our current models and highlighting the need for future studies to explore these regions in greater detail. The addition reads: “…Our models excluded the N-terminal PAS domain due to GPU memory limitations, despite its inclusion in initial templates. This omission may overlook its potential roles in gating kinetics and allosteric effects on drug binding (e.g., PMID: 21449979, PMID: 23319729, PMID: 29706893, PMID: 30826123, DOI:10.4103/jpp.JPP_158_17). Future research will explore the full-length hERG channel with enhanced computational resources to assess these regions’ contributions to conformational state transitions and pharmacology.”

      (2) In the second-to-last paragraph of the Introduction, the authors describe how AlphaFold2 works. They write, “AlphaFold2 primarily requires the amino acid sequence of a protein as its input, but the method utilizes other key elements: in addition to the amino acid sequence, AlphaFold2 can also utilize multiple sequence alignments (MSAs) of similar sequences from different species, templates of related protein structures when available, and/or homologous proteins (Jumper et al., 2021a). Evolutionarily conserved regions over multiple isoforms and species indicated that the sequence is crucial for structural integrity”. The last sentence is confusing; if the authors mean that all information required to fold the protein into its 3D structure is present in its primary sequence, that has been the paradigm. It is unclear from this paragraph what the authors wanted to convey.

      We apologize for any confusion caused by this phrasing. Our intent was not to restate the well-established paradigm that a protein’s primary sequence contains the information needed for its 3D structure, but rather to emphasize how

      AlphaFold2 leverages evolutionary conservation, via multiple sequence alignments (MSAs), to infer structural constraints beyond what a single sequence alone might reveal. Specifically, we aimed to highlight that conserved regions across species and isoforms provide additional context that AlphaFold2 uses to enhance the accuracy of its predictions, complementing the use of templates and homologous structures as described in Jumper et al. (2021). To clarify this, we revised the sentence in the manuscript to read: “AlphaFold2 primarily requires a protein's amino acid sequence as input, but it also leverages other critical data sources. In addition to the sequence, it incorporates multiple sequence alignments (MSAs) of related proteins from different species, available structural templates, and information on homologous proteins. While the primary sequence encodes the 3D structure, AlphaFold2 harnesses evolutionary conservation from MSAs to reveal structural insights that extend beyond what a single sequence can provide.” We thank the reviewer for pointing out this ambiguity.

      (3) In the Results section, the authors state that the predictions generated by their method are evaluated by standard accuracy metrics, please elaborate - what standard metrics were used to judge the predictions and why (some references would be a nice addition). Further, on Page 6, the sentence “There are fewer differences between the open- and closed-state models (Figure S2b, d)” is confusing, fewer differences than what? or there are a few differences between the two states/models? Please clarify.

      The original sentence referring to “standard accuracy metrics” is somewhat misplaced, as our intent was not to apply any conventional “benchmarking” to judge the predictions, but rather to evaluate functional and structural relevance in a physiologically meaningful context. Specifically, we assessed drug binding affinities from molecular docking simulations (in Rosetta Energy Units, R.E.U.) against experimental drug potency data (e.g., IC<sub>50</sub> values converted to free energies in kcal/mol, Figure 7), analyzed differences in interaction networks across states in relation to known mutations affecting hERG inactivation (Figure 4, Table 2), validated ion conduction properties through MD simulations with the applied voltage against expected state-dependent hERG channel behavior (Figure 5), and compared predicted structural models to available experimental cryo-EM structures (Figure 3). We clarified in the text that our assessment emphasized the physiological plausibility of the generated conformations, drawing on evidence from existing computational and experimental studies at each step of the analysis above.

      As for the sentence on page 6, “There are fewer differences between the open- and closed-state models,” we apologize for the ambiguity; we meant that the hydrogen bond networks in the selectivity filter region exhibit fewer differences between the open and closed states compared to the more pronounced variations seen between the open and inactivated states. We revised this sentence to read: “The open- and closed-state models show fewer differences in their selectivity filter hydrogen bond networks compared to those between the open and inactivated states,” to enhance readability.

      (4) In the Discussion, the authors reiterate that this methodology can be extended to sample multiple protein conformations, and their system of choice was hERG potassium channel. I think this methodology can be applied to a system when there is enough knowledge of static structures, and some information on dynamics (through simulations) and mutagenesis analysis available. A well-studied system can benefit from such a protocol to gauge other conformational states.

      We agree that this approach is well-suited to systems with sufficient static structures, dynamic insights from simulations, and mutagenesis data, as seen with the hERG channel. We appreciate the reviewer’s implicit concern about generalizability to less-characterized systems and addressed this in the Discussion as a limitation, noting that the method’s effectiveness may depend on prior knowledge. Future studies can explore whether the advent of AlphaFold3 and other deep learning approaches can enhance its applicability to systems with more limited data. We have added this comment to the Discussion: “…A limitation of our methodology is its reliance on well-characterized systems with ample static structures, molecular dynamics simulation data, and mutagenesis insights, as demonstrated with the hERG channel, which may limit its applicability to less-studied proteins.”

      (5) The Methods section must be broken down into steps to make it easier to follow for the reader (if they want to implement these steps for themselves on their system of choice).

      a. Is possible to share example scripts and code used to piece templates together for AF2. Also, since the AF3 code is now available, the authors may comment on how their protocol can be applicable there or have plans to implement their protocol using AF3 (which is designed to work better for binding small molecules). Please see https://github.com/google-deepmind/alphafold3 for the recently released code for AF3.

      We appreciate the reviewer’s suggestion to improve the Methods section and their comments on scripts and AlphaFold3 (AF3). We revised the Methods to separate it into clear steps (e.g., template preparation, AF2 setup, clustering, and refinement) for better readability and reproducibility, and uploaded the sample scripts along with the instructions to GitHub (https://github.com/k-ngo/AlphaFold_Analysis).

      Regarding AF3’s recent code release, we plan to explore the applicability of our methodology to AF3 in a follow-up study, leveraging its advanced features to refine conformational predictions and state-specific drug docking, and added a brief comment to the Discussion to reflect this future direction: “…Following the recent release of AlphaFold3’s source code, we plan to explore the applicability of our template-guided methodology in a follow-up study, leveraging AF3’s advanced diffusion-based architecture to enhance protein conformational state predictions and state-specific drug docking, particularly given its improved capabilities for modeling small molecule – protein interactions…”

      b. The authors modified the hERG protein by removing a segment, the N-terminal PAS domain (residues M1 - R397) because of graphics card memory limitation. Would the removal of the PAS domain affect the structure and function of the channel protein? HERG and other members of the “eag K<sup>+</sup> channel” family contain a PAS domain on their cytoplasmic N terminus. Removal of this domain alters a physiologically important gating transition in HERG, and the addition of the isolated domain to the cytoplasm of cells expressing truncated HERG reconstitutes wild-type gating. (see https://doi.org/10.1371/journal.pone.0059265). Please elaborate on this.

      We thank the reviewer for raising an important point about the removal of the N-terminal PAS domain and for highlighting its physiological role in hERG channel gating transitions. In our study, unlike experimental settings where PAS removal alters gating, we believe this omission has minimal impact on our key analyses.

      The drug docking procedure focuses on optimizing drug binding poses with minor protein structural refinement around the putative drug binding site, which in our case is the hERG channel pore region, where hERG-blocking drugs predominantly bind. The cytoplasmic PAS domain, located distally from this site, remains outside the protein structure refinement zone during drug docking simulations. However, one aspect we have not yet considered is the potential effect of drug modulation of the hERG channel gating and vice versa particularly given the PAS domain’s role in gating. This interplay could be significant but requires investigation beyond our current drug docking framework. We plan to explore this in future studies using alternative simulation methodologies, such as extended MD simulations or enhanced sampling techniques, to comprehensively capture these dynamic protein - ligand interactions.

      Similarly, in our 1 μs long MD simulations assessing ion conductivity (Figure 4), the timescale is too short for PASmediated gating changes to propagate through the protein and meaningfully influence ion conduction and channel activation dynamics, which occurs on a millisecond time scale (see e.g., DOI: 10.3389/fphys.2018.00207). To fully address this limitation, we plan to explore the inclusion of the PAS domain in a follow-up study with enhanced computational resources, allowing us to investigate its structural and functional contributions more comprehensively.

      (6) The first paragraph of the Methods reads as though AF2 has layers that recycle structures. We doubt that the authors meant it that way. Please update the language to clarify that recycling is an iterative process in which the pairwise representation, MSA, and predicted structures are passed (“recycled”) through the model multiple times to improve predictions.

      We agree that the phrasing might suggest physical layers recycling structures, which was not our intent. Instead, we meant to describe AlphaFold2’s iterative refinement process, where intermediate outputs, such as the pairwise residue representations, multiple sequence alignments (MSAs), and predicted structures, are iteratively passed (or “recycled”) through the model to enhance prediction accuracy. To clarify this, we revised the relevant sentence to read: “A critical feature of AlphaFold2 is its iterative refinement, where pairwise residue representations, MSAs, and initial structural predictions are recycled through the model multiple times, improving accuracy with each iteration.”

      Reviewer #3 (Recommendations for the authors):

      The authors should integrate the very recently published CryoEM experimental data of hERG inhibition by several drugs (Miyashita et al., Structure, 2024; DOI: 10.1016/j.str.2024.08.021).

      We thank the reviewer for the suggestion. Here, we compare drug binding in our open-states (PDB 5VA2-derived and an additional AlphaFold-predicted model from Cluster 3 of inactivated-state-sampling attempt named “AF ic3”) and inactivated-state models, using the cationic forms of astemizole and E-4031, with the corresponding experimental structures (Figure S13). Drug binding in the closed state is excluded as the pore architecture deviates too much from those in the cryo-EM structures. Experimental data (DOI: 10.1124/mol.108.049056) indicate that both astemizole and E4031 bind more potently to the inactivated state of the hERG channel.

      Astemizole (Figure S13a):

      - In the PDB 5VA2-derived open-state model, astemizole binds centrally within the pore cavity, adopting a bent conformation that allows both aromatic ends of the molecule to engage in π–π stacking with the side chains of Y652 from two opposing subunits. Hydrophobic contacts are observed with S649 and F656 residues.

      - In the AF ic3 open-state model, the ligand is stabilized through multiple π–π stacking interactions with Y652 residues from three subunits, forming a tight aromatic cage around its triazine and benzimidazole rings. Hydrophobic interactions are observed with hERG residues T623, S624, Y652, F656, and S660.

      - In the inactivated-state model, astemizole adopts a compact, horizontally oriented pose deeper in the channel pore, forming the most extensive interaction network among all the states. The ligand is tightly stabilized by multiple π–π stacking interactions with Y652 residues across three subunits, and forms hydrogen bonds with residues S624 and Y652. Additional hydrophobic contacts are observed with residues F557, L622, S649, and Y652.

      - Consistent with our findings, electrophysiology study by Saxena et al. identified hERG residues F557 and Y652 as crucial for astemizole binding, as determined through mutagenesis (DOI: 10.1038/srep24182).

      - In the cryo-EM structure (PDB 8ZYO) (DOI: 10.1016/j.str.2024.08.021), astemizole is stabilized by π–π stacking with Y652 residues. However, no hydrogen bonds are detected which may reflect limitations in cryo-EM resolution rather than true absence of contacts. Additional hydrophobic interacts are observed with L622 and G648 residues.

      E-4031 (Figure S13b):

      - In the PDB 5VA2-derived open-state model, E-4031 binds within the central cavity primarily through polar interactions. It forms a π–π stacking interaction with residue Y652, anchoring one end of the molecule. Polar interactions are observed with residues A653 and S660. Additional hydrophobic contacts are observed with residues A652 and Y652.

      - In the AF ic3 open-state model, E-4031 adopts a slightly deeper pose within the central cavity stabilized by dual π–π stacking interactions between its aromatic rings and hERG residue Y652. Additional hydrogen bonds are observed with residues S624 and Y652, and hydrophobic contacts are observed with residues T623 and S624.

      - In the inactivated-state model, E-4031 adopts its deepest and most stabilized binding pose, consistent with its experimentally observed preference for this state. The ligand is stabilized by multiple π–π stacking interactions between its aromatic rings and hERG residues Y652 from opposing subunits. The sulfonamide nitrogen engages in hydrogen bonding with residue S649, while the piperidine nitrogen hydrogen bonds with residue Y652. Hydrophobic contacts with residues S624, Y652, and F656 further reinforce the binding, enclosing the ligand in a densely packed aromatic and polar environment.

      - Previous mutagenesis study showed that mutations involving hERG residues F557, T623, S624, Y652, and F656 affect E-4031 binding (DOI: 10.3390/ph16091204).

      - In the cryo-EM structure (PDB 8ZYP) (DOI: 10.1016/j.str.2024.08.021), E-4031 engages in a single π–π stacking interaction with hERG residue Y652, anchoring one end of the molecule. The remainder of the ligand is stabilized predominantly through hydrophobic contacts involving residues S621, L622, T623, S624, M645, G648, S649, and additional Y652 side chains, forming a largely nonpolar environment around the binding pocket.

      In both cryo-EM structures, astemizole and E-4031 adopt binding poses that closely resembles the inactivated-state model in our docking study, consistent with experimental evidence that these drugs preferentially bind to the inactivated state (DOI: 10.1124/mol.108.049056). This raises the possibility that the cryo-EM structures may capture an inactivatedlike channel state. However, closer examination of the SF reveals that the cryo-EM conformations more closely resemble the open-state PDB 5VA2 structure (DOI: 10.1016/j.cell.2017.03.048), which has been shown to be conductive here and in previous studies (DOI: 10.1073/pnas.1909196117, 10.1161/CIRCRESAHA.119.316404).

      The conformational differences between the cryo-EM and open-state docking results may reflect limitations of the docking protocol itself, as GALigandDock assumes a rigid protein backbone and cannot account for ligand-induced large conformational changes. In our open-state models, the hydrophobic pocket beneath the selectivity filter is too small to accommodate bulky ligands (Figure 3a, b), whereas the cryo-EM structures show a slight outward shift in the S6 helix that expands this space (Figure S13).These allosteric rearrangements, though small, falls outside the scope of the current docking protocol, which lacks flexibility to capture these local, ligand-induced adjustments (DOI: 10.3389/fphar.2024.1411428).

      In contrast, docking to the AlphaFold-predicted inactivated-state model reveals a reorganization beneath the selectivity filter that creates a larger cavity, allowing deeper ligand insertion. Notably, neither our inactivated-state docking nor the available cryo-EM structures show strong interactions with F656 residues. However, in the AlphaFold-predicted inactivated model, the more extensive protrusion of F656 into the central cavity may further occlude the drug’s egress pathway, potentially trapping the ligand more effectively. This could explain why mutation of F656 significantly reduces the binding affinity of E-4031 (DOI: 10.3390/ph16091204). These findings suggest that inactivation may trigger a series of modular structural rearrangements that influence drug access and binding affinity, with different aspects potentially captured in various computational and experimental studies, rather than resulting from a single, uniform conformational change.

      Discussion of the original Wang and Mackinnon finding, DOI: 10.1016/j.cell.2017.03.048 regarding C-inactivation, pore mutation S631A and F627 rearrangement is likely warranted. Since hERG inactivation is present at 0 mV in WT channels (the likely voltage for the CryoEM study) please discuss how this might affect interpretations of starting with this structure as a template for models presented here, perhaps as part of Figure S1.

      We sincerely thank the reviewer for bringing up the insightful findings from Wang and MacKinnon regarding hERG C-type inactivation as well as the voltage context of their cryo-EM structure (PDB 5VA2). We recognize that WT hERG exhibits inactivation at 0 mV, likely the condition of the cryo-EM study, raising the possibility that PDB 5VA2, while classified as an open state, might subtly reflect features of inactivation. Notably, PDB 5VA2 has been widely adopted in numerous studies and consistently found to represent a conducting state, such as in Yang et al. (DOI: 10.1161/CIRCRESAHA.119.316404) and Miranda et al. (DOI: 10.1073/pnas.1909196117). Our MD simulations further support this, showing K<sup>+</sup> conduction in the 5VA2-based open-state model (Figure 4a, c), consistent with its selectivity filter conformation (Figure S1a). Although we used PDB 5VA2 as a starting template for predicting inactivated and closed states, our AlphaFold2 predictions did not rigidly adhere to this structure, as evidenced by distinct differences in hydrogen bond networks, drug binding affinities, pore radii, and ion conductivity between our state-specific hERG channel models (Figures S2, 5, 3b, 4). Nevertheless, this does not preclude the possibility that PDB 5VA2’s certain potential inactivated-like traits at 0 mV could subtly influence our predictions elsewhere in the model, which warrants further exploration in future studies. In our revised analysis, we also tested an alternative AlphaFold-predicted conformation, referred to as Open (AlphaFold cluster 3), which, while sharing some similarities with PDB 5VA2, exhibits subtle differences in the selectivity filter and pore conformations. This structure was also found to be conducting ions and showed a drug binding profile similar to that of the PDB 5VA2-based open-state model. We greatly appreciate this feedback which helped us refine and strengthen our analysis.

      Page 8, the significance of 750 and 500 mV in terms of physiological role?

      We appreciate this opportunity to clarify the methodological rationale. Although these voltages significantly exceed typical physiological membrane potentials, their use in MD simulations is a well-established practice to accelerate ion conduction events. This approach helps overcome the inherent timescale limitations of conventional MD simulations, as demonstrated in previous studies of hERG and other ion channels. For instance, Miranda et al. (DOI: 10.1073/pnas.1909196117), Lau et al. (DOI: 10.1038/s41467-024-51208-w), Yang et al. (DOI: 10.1161/CIRCRESAHA.119.316404) applied similarly high voltages (500~750 mV) to study hERG K<sup>+</sup> conduction, which is notably small under physiological conditions at ~2 pS (DOI: 10.1161/01.CIR.94.10.2572), necessitating amplification to observe meaningful permeation within nanosecond-to-microsecond timescales. Likewise, studies of other K<sup>+</sup> ion channels, such as Woltz et al. (DOI: 10.1073/pnas.2318900121) on small-conductance calcium-activated K<sup>+</sup> channel SK2 and Wood et al. (DOI: 10.1021/acs.jpcb.6b12639) on Shaker K<sup>+</sup> channel, have used elevated voltages (250~750 mV) to probe ion conduction mechanisms via MD simulations. In addition, the typical timescale of these simulations (1 μs) is too short to capture major structural effects such as those leading to inactivation or deactivation which occur over milliseconds in physiological conditions.

      The abstract could be edited a bit to more clearly state the novel findings in this study.

      We thank the reviewer for their suggestion. We have revised the abstract to read: “To design safe, selective, and effective new therapies, there must be a deep understanding of the structure and function of the drug target. One of the most difficult problems to solve has been resolution of discrete conformational states of transmembrane ion channel proteins. An example is K<sub>V</sub>11.1 (hERG), comprising the primary cardiac repolarizing current, I<sub>kr</sub>. hERG is a notorious drug antitarget against which all promising drugs are screened to determine potential for arrhythmia. Drug interactions with the hERG inactivated state are linked to elevated arrhythmia risk, and drugs may become trapped during channel closure. While prior studies have applied AlphaFold to predict alternative protein conformations, we show that the inclusion of carefully chosen structural templates can guide these predictions toward distinct functional states. This targeted modeling approach is validated through comparisons with experimental data, including proposed state-dependent structural features, drug interactions from molecular docking, and ion conduction properties from molecular dynamics simulations. Remarkably, AlphaFold not only predicts inactivation mechanisms of the hERG channel that prevent ion conduction but also uncovers novel molecular features explaining enhanced drug binding observed during inactivation, offering a deeper understanding of hERG channel function and pharmacology. Furthermore, leveraging AlphaFold-derived states enhances computational screening by significantly improving agreement with experimental drug affinities, an important advance for hERG as a key drug safety target where traditional single-state models miss critical state-dependent effects. By mapping protein residue interaction networks across closed, open, and inactivated states, we identified critical residues driving state transitions validated by prior mutagenesis studies. This innovative methodology sets a new benchmark for integrating deep learning-based protein structure prediction with experimental validation. It also offers a broadly applicable approach using AlphaFold to predict discrete protein conformations, reconcile disparate data, and uncover novel structure-function relationships, ultimately advancing drug safety screening and enabling the design of safer therapeutics.”

      Many of the Supplemental figures would fit in better in the main text, if possible, in my opinion. For instance, the network analysis (Fig. S2) appears to be novel and is mentioned in the abstract so may fit better in the main text. The discussion section could be focused a bit more, perhaps with headers to highlight the key points.

      Yes, we agree with the reviewer and made the suggested changes. We moved Figure S2 as a new main-text figure.

      Additionally, we revised the Discussion section to improve focus and clarity.

    1. Joint Public Review:

      Summary:

      The authors identify a novel relationship between exosome secretion and filopodia formation in cancer cells and neurons. They observe that multivesicular endosomes (MVE)-plasma membrane (PM) fusion is associated with filopodia formation in HT1080 cells and that MVEs are present on filopodia in primary neurons. Using overexpression and knockdown (KD) of Rab27/HRS in HT1080 cells, melanoma cells and/or primary rat neurons, they find that decreasing exosome secretion reduces filopodia formation, while Rab27 overexpression leads to the opposite result. Furthermore, the decreased filopodia formation is rescued in the Rab27a/HRS KD melanoma cells by the addition of small extracellular vesicles (EVs) but not large EVs purified from control cells. The authors identify endoglin as a protein unique to small EVs secreted by cancer cells when compared to large EVs. KD of endoglin reduces filopodia formation and this is rescued by the addition of small EVs from control cells and not by small EVs from endoglin KD cells. Based on the role of filopodia in cancer metastasis, the authors then investigate the role of endoglin in cancer cell metastasis using a chick embryo model. They find that injection of endoglin KD HT1080 cells into chick embryos gives rise to less metastasis compared to control cells - a phenotype that is rescued by the co-injection of small EVs from control cells. Using quantitative mass spectrometry analysis, they find that thrombospondin type 1 domain containing 7a protein (THSD7A) is down regulated in small EVs from endoglin KD melanoma cells compared to those from control cells. They also report that THSD7A is more abundant in endoglin KD cell lysate compared to control HT1080 cells and less abundant in small EVs from endoglin KD cells compared to control cells, indicating a trafficking defect. Indeed, using immunofluorescence microscopy, the authors observe THSD7A-mScarlet accumulation in CD63-positive structures in endoglin KD HT1080 cells, compared to control cells. Finally, the authors determine that exosome-secreted THSD7A induces filopodia formation in a Cdc42-dependent mechanism.

      Strengths:

      Through proteomic analysis, the authors revealed that endoglin is an important player in the effective trafficking of THSD7A within exosomes. This study offers interesting insights into the dynamic interplay between exosome-mediated protein trafficking and essential cellular processes, emphasizing its significant relevance in both cancer progression and neural function. The authors communicated their findings clearly and effectively.

      (1) While exosomes are known to play a role in cell migration and autocrine signaling, the relationship between exosome secretion and the formation of filopodia is novel.

      (2) The authors identify an exosomal cargo protein, THSD7A, which is essential for regulating this function.

      (3) The data presented provide strong evidence of a role for endoglin in the trafficking of THSD7A in exosomes.

      (4) The authors associate this process with functional significance in cancer cell metastasis and neurological synapse formation, both of which involve the formation of filopodia.

      (5) The data are presented clearly, and their interpretation appropriately explains the context and significance of the findings.

      Weaknesses:

      While the authors showed the important role of exosomal cargo protein THSD7A in neurons, it will be interesting to conduct any in vivo studies to determine whether THSD7A plays a similar role in promoting filopodia and synapse formation in vivo. Some of the comments of the reviewers were not fully addressed, such as rigorous analysis and quantification through Live-cell imaging through TIRF microscopy tracking labeled THSD7A and filopodia formation, which would provide more clarity in timing and strengthen causality of this relationship. The authors need to consider fully characterizing the role of Cdc42. If the authors would like to fully elaborate on the role of Cdc42 in another manuscript, it is better not to mention at all the role of Cdc42 in filopodia formation in this paper.

    2. Author response:

      The following is the authors’ response to the original reviews

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      The study significantly advances our understanding of how exosomes regulate filopodia formation. Filopodia play crucial roles in cell movement, polarization, directional sensing, and neuronal synapse formation. McAtee et al. demonstrated that exosomes, particularly those enriched with the protein THSD7A, play a pivotal role in promoting filopodia formation through Cdc42 in cancer cells and neurons. This discovery unveils a new extracellular mechanism through which cells can control their cytoskeletal dynamics and interaction with their surroundings. The study employs a combination of rescue experiments, live-cell imaging, cell culture, and proteomic analyses to thoroughly investigate the role of exosomes and THSD7A in filopodia formation in cancer cells and neurons. These findings offer valuable insights into fundamental biological processes of cell movement and communication and have potential implications for understanding cancer metastasis and neuronal development.

      Weaknesses:

      The conclusions of this study are in most cases supported by data, but some aspects of data analysis need to be better clarified and elaborated. Some conclusions need to be better stated and according to the data observed.

      We appreciate the reviewer's recognition of the impact of our study. We will address the concerns about data analysis and the statement of our conclusions in our full response to reviewers.

      Reviewer #2 (Public review):

      Summary:

      The authors show that small EVs trigger the formation of filopodia in both cancer cells and neurons. They go on to show that two cargo proteins, endoglin, and THSD7A, are important for this process. This possibly occurs by activating the Rho-family GTPase CDC42.

      Strengths:

      The EV work is quite strong and convincing. The proteomics work is well executed and carefully analyzed. I was particularly impressed with the chick metastasis assay that added strong evidence of in vivo relevance.

      Weaknesses:

      The weakest part of the paper is the Cdc42 work at the end of the paper. It is incomplete and not terribly convincing. This part of the paper needs to be improved significantly

      We appreciate the reviewer's recognition of the impact of our study. Indeed, more work needs to be done to clarify the role of Cdc42 in the induction of filopodia by exosome-associated THSD7A. We anticipate that this will be a separate manuscript, delving in-depth into how exosome-associated THSD7A interacts with recipient cells to activate Cdc42 and carrying out a variety of assays for Cdc42 activation.

      Reviewer #3 (Public review):

      Summary:

      The authors identify a novel relationship between exosome secretion and filopodia formation in cancer cells and neurons. They observe that multivesicular endosomes (MVE)-plasma membrane (PM) fusion is associated with filopodia formation in HT1080 cells and that MVEs are present in filopodia in primary neurons. Using overexpression and knockdown (KD) of Rab27/HRS in HT1080 cells, melanoma cells, and/or primary rat neurons, they found that decreasing exosome secretion reduces filopodia formation, while Rab27 overexpression leads to the opposite result. Furthermore, the decreased filopodia formation is rescued in the Rab27a/HRS KD melanoma cells by the addition of small extracellular vesicles (EVs) but not large EVs purified from control cells. The authors identify endoglin as a protein unique to small EVs secreted by cancer cells when compared to large EVs. KD of endoglin reduces filopodia formation and this is rescued by the addition of small EVs from control cells and not by small EVs from endoglin KD cells. Based on the role of filopodia in cancer metastasis, the authors then investigate the role of endoglin in cancer cell metastasis using a chick embryo model. They find that injection of endoglin KD HT1080 cells into chick embryos gives rise to less metastasis compared to control cells - a phenotype that is rescued by the co-injection of small EVs from control cells. Using quantitative mass spectrometry analysis, they find that thrombospondin type 1 domain containing 7a protein (THSD7A) is downregulated in small EVs from endoglin KD melanoma cells compared to those from control cells. They also report that THSD7A is more abundant in endoglin KD cell lysate compared to control HT1080 cells and less abundant in small EVs from endoglin KD cells compared to control cells, indicating a trafficking defect. Indeed, using immunofluorescence microscopy, the authors observe THSD7A-mScarlet accumulation in CD63-positive structures in endoglin KD HT1080 cells, compared to control cells. Finally, the authors determine that exosome-secreted THSD7A induces filopodia formation in a Cdc42-dependent mechanism.

      Strengths:

      (1) While exosomes are known to play a role in cell migration and autocrine signaling, the relationship between exosome secretion and the formation of filopodia is novel.

      (2) The authors identify an exosomal cargo protein, THSD7A, which is essential for regulating this function.

      (3) The data presented provide strong evidence of a role for endoglin in the trafficking of THSD7A in exosomes.

      (4) The authors associate this process with functional significance in cancer cell metastasis and neurological synapse formation, both of which involve the formation of filopodia.

      (5) The data are presented clearly, and their interpretation appropriately explains the context and significance of the findings.

      Weaknesses:

      (1) A better characterization of the nature of the small EV population is missing:

      It is unclear why the authors chose to proceed to quantitative mass spectrometry with the bands in the Coomassie from size-separated EV samples, as there are other bands present in the small EV lane but not the large EV lane. This is important to clarify because it underlies how they were able to identify THSD7A as a unique regulator of exosome-mediated filopodia formation. Is there a reason why the total sample fractions were not compared? This would provide valuable information on the nature of the small and large EV populations.

      We would like to clarify that there are two sets of proteomics data in the manuscript. The first was comparing bands from a colloidal Coomassie-stained gel from two samples: small EVs and large EVs from B16F1 cells. In this proteomics experiment, we identified endoglin as present in small EVs, but not large EVs. For this experiment, we only sent four bands from the small EV lane, chosen based on their obvious banding pattern difference on the Coomassie gel.

      In the second proteomics experiment, we used quantitative iTRAQ proteomics to compare small EVs purified from B16F1 control (shScr) and endoglin KD (shEng1 and shEng2) cell lines. In this experiment, we sent total protein extracted from small EV samples for analysis. So, these samples included the entire EV content, not just selected bands from a gel. In this experiment, we identified THSD7A as reduced in the shEng small EVs.

      (2) Data analysis and quantification should be performed with increased rigor:

      a) Figure 1C - The optical and temporal resolution are insufficient to conclusively characterize the association between exosome secretion and filopodia. Specifically, the 10-second interval used in the image acquisitions is too close to the reported 20-second median time between exosome secretion and filopodia formation. Two-5 sec intervals should be used to validate this. It would also be important to correlate the percentage of filopodia events that co-occur with exosome secretion. Is this a phenomenon that occurs with most or only a small number of filopodia? Additionally, resolution with typical confocal microscopy is subpar for these analyses. TIRF microscopy would offer increased resolution to parse out secretion events. As the TIRF objective is listed in the Methods section, figure legends should mention which images were acquired using TIRF microscopy.

      We acknowledge that the frame rate naturally limits our estimates of the timing of filopodia formation after exosome secretion. We set out to show a relationship between exosome secretion and filopodia formation, based on their proximity in timing. While our data set shows a median time interval of 20 seconds, the true median could be between 10-30 seconds, based on our frame rate. Regardless of the exact timing, our data show that exosome secretion is rapidly followed by filopodia formation events.

      To address the question of the percentage of filopodia events that are preceded by exosome secretion, the reviewer is correct in stating that we might need TIRF microscopy and a faster frame rate to observe all the MVB fusion events and get an accurate calculation of this number. The timing of the acquisition was based on the typical timing of filopodia formation, which is slow relative to MVB fusion. Thus, with the current dataset, we could miss secretion events taking place between the 10 second time intervals. Therefore, to address this question, we would need to acquire a new dataset with a much more rapid frame acquisition (multiple frames per second rather than one frame every ten seconds). Regardless, for the secretion events that we visualized with the current dataset, we always observed subsequent filopodia formation.

      No TIRF imaging was used in this manuscript. A TIRF objective was used for selected neuron imaging (see methods); however, it was used for spinning disk confocal microscopy, not for TIRF imaging. This is stated in the methods.

      b) Figure 2 - It would be important to perform further analysis to concretely determine the relationship between exosome secretion and filopodia stability. Are secretion events correlated with the stability of filopodia? Is there a positive feedback loop that causes further filopodia stability and length with increased secretion? Furthermore, is there an association between the proximity of secretion with stability? Quantification of filopodia more objectively (# of filopodia/cell) would be helpful.

      Our data show that manipulation of general exosome secretion, via Hrs knockdown, affects both de novo filopodia formation and filopodia stability (Fig 2g,h). Interestingly, knockdown of endoglin only affects de novo filopodia formation, while filopodia stability is unaffected (Fig 4g,h). These results suggest that filopodia stability is dependent upon exosome cargoes besides endoglin/THSD7A. Such cargoes might include other extracellular matrix molecules, such as fibronectin. We previously showed that exosomes promote nascent cell adhesion and rapid cell migration, through exosome-bound fibronectin (Sung et al., Nature Communications, 6:7164, 2015). We also previously found that inhibition of exosome secretion affects the persistence of invadopodia, which are filopodia-dependent structures (Hoshino et al., Cell Reports, 5:1159-1168, 2013). We agree that this is an interesting research direction, and perhaps future work could focus on exosomal factors that are responsible for filopodia persistence. This would possibly involve more proteomics analysis to identify candidate exosomal cargoes involved in this process.

      With regard to the way we plotted the filopodia data, we plotted the cancer cell data as filopodia per cell area so that it matched the neuron data, which was plotted as filopodia per 100 µm of dendrite distance. Since the neurons cannot be imaged as a whole cell, the quantification is based on the length of the dendrite in the image. We found that graphing the cancer cell data as filopodia per cell gave similar results as filopodia per cell area. To demonstrate that this quantification gives similar results, we have now plotted the filopodia per cell area data from Fig 2 as filopodia per cell and placed these new plots in Supp Fig 2.

      c) Figure 6 - Why use different gel conditions to detect THSD7A in small EVs from B16F1 cells vs HT1080 and neurons? Why are there two bands for THSD7A in panels C and E? It is difficult to appreciate the KD efficiency in E. The absence of a signal for THSD7A in the HT1080 shEng small EVs that show a signal for endoglin is surprising. The authors should provide rigorous quantification of the westerns from several independent experimental repeats.

      Detection of THSD7A via Western blot was, unfortunately, not straightforward and simple. Due to the large size (~260 kDa) of THSD7A, its low level of expression in cancer cells, as well as the inconsistency of commercially available THSD7A antibodies, we had to troubleshoot multiple conditions. We found that it was much easier to detect THSD7A in the human fibrosarcoma cell line HT1080 than in the mouse B16F1 cells, both in the cell lysates and in the small EVs. We were unable to detect THSD7A using the same (reducing) conditions for the mouse melanoma B16F1 samples but were successful using native gel conditions. We also detected THSD7A in rat primary neuron samples. All these samples were from different source organisms (human, mouse, rat) and from either cell lysates or extracellular vesicles, further complicating the analyses. Expression and maturation of THSD7A in these different cell types and compartments could involve different post-translational modifications, such as glycosylation, thus requiring different methods needed to detect THSD7A on Western blots and leading to different banding patterns.

      With regard to the level of knockdown of THSD7A in the Western blot shown in Figure 6E, the normalized level is quantitated below the bands. If you compare that quantitation to the filopodia phenotypes in the same panel, they are quite concordant. Figures 7B and 7C show quantification of triplicate Western blots, highlighting the significant accumulation of THSD7A in shEng cell lysates, as well as significant small EV secretion of THSD7A in control and WT rescued conditions.

      (3) The study lacks data on the cellular distribution of endoglin and THSD7A:

      a) Figure 6 - Is THSD7A expected to be present in the nucleus as shown in panel D (label D is missing in the Figure). It is not clear if this is observed in neurons. a Western of endogenous THSD7A on cell fractions would clarify this. The authors should further characterize the cellular distribution of THSD7A in both cell types. Similarly, the cellular distribution of endoglin in the cancer cells should be provided. This would help validate the proposed model in Figure 8.

      The image in figure 6D shows an HT1080 cell stained with phalloidin-Alexa Fluor 488 to visualize F-actin with or without expression of THSD7A-mScarlet. In order to fully visualize the thin filopodia protrusions, the cellular plane of focus of the images for this panel was purposely taken at the bottom of the cell, where the cell is attached to the coverslip glass. Thus, we interpret the red signal across the cell body as THSD7A-mScarlet expression on the plasma membrane underneath the cell, not in the nucleus. The neuron images only include the dendrite portion of the neurons; therefore, there is no nucleus present in the neuronal images. For the cellular distribution of endoglin, we agree that this is an important future direction to understand how endoglin regulates THSD7A trafficking. We have added the lack of these data to the “Limitations” section at the end of the manuscript.

      b) Figure 7 - Although the western blot provides convincing evidence for the role of endoglin in THSD7A trafficking, the microscopy data lack resolution as well as key analyses. While differences between shSCR and shEng cells are clear visually, the insets appear to be zoomed digitally which decreases resolution and interferes with interpretation. It would be crucial to show the colocalization of endoglin and THSD7A within CD63-postive MVE structures. What are the structures in Figure 7E shSCR zoom1? It would be important to rule out that these are migrasomes using TSPAN4 staining. More information on how the analysis was conducted is needed (i.e. how extracellular areas were chosen and whether the images are representative of the larger population). A widefield image of shSCR and shEng cells and DAPI or HOECHST staining in the higher magnification images should be provided. Additionally, the authors should quantify the colocalization of external CD63 and mScarlet signals from many independently acquired images (as they did for the internal signals in panel F). Is there no external THSD7A signal in the shEng cells?

      The images for Figure 7E were taken with high resolution on a confocal microscope. Insets for Figure 7E were digitally zoomed so that readers could see the tiny structures. Zoom 1 in Figure 7E shows areas of extracellular deposition, whereas Zoom 2 shows THSD7A colocalization with CD63 in MVE. In the extracellular areas (Zoom 1), we observe small punctate depositions that are positive for CD63 and/or THSD7A-mScarlet. Our interpretation of this staining is that the cells are secreting heterogeneous small EVs that are then attached to the glass coverslip. The images and zooms in Fig 7E were chosen to be representative and indeed reveal that there is more extracellular deposition of THSD7A-mScarlet outside the control shScr cells compared to the shEng cells, consistent with more secretion of THSD7A in small EVs from shScr cells when compared to those of shEng cells (Fig 7A,B). However, we did not quantify this difference, as these experiments were conducted with transient transfection of THSD7A-mScarlet, and it is challenging to determine which cell the extracellular THSD7A-mScarlet came from, complicating any quantitative analysis on a per-cell basis.

      Quantification of internal THSD7A localization is much more straightforward in this experimental regime. Indeed, in Figure 7F, we quantitated internal colocalization of THSD7A-mScarlet and CD63, which we obtained by choosing only cells that were visually positive for THSD7A-mScarlet in each transient transfection and omitting all extracellular signals. Quantifying the extracellular colocalization of THSD7A and CD63 could certainly be a future direction for this project and would require establishing cells that stably express THSD7A-mScarlet.

      With regard to whether the extracellular deposits are migrasomes, we have no reason to believe that they would be migrasomes. The preponderance of our evidence points to exosomes as carrying THSD7A and inducing filopodia. Furthermore, CD63 is an exosome marker (Sung et al., Nat Comm, 2020) and does not induce migrasomes, unlike many other tetraspanins (Huang et al., Nat Cell Bio, 2019).

      Recommendations for the authors:

      Reviewer #1 (Recommendations for the authors):

      The authors need to clarify the figure labeling and description and conclusions would be better to be drawn based on the findings. Some figures need to more clear e.g. Figure 1E needs to have information on what are green and red fluorescent proteins. Do all figures in 1A have the same scale bar or different? Figure 3A lacks a scale bar. In Figure 3, the GFP signal is in yellow, does it represent a merge or is it just the GFP alone? Figure 6D is missing a D. Figure 4D needs to be better explained. Additionally, both figures 8B and 8C since represent a model based on all the findings of the study would be better to stand alone as a separate figure from figure 8A.

      The figure legend for figure 1E notes that green corresponds to GFP-Rab27b and the red corresponds to mCherry filler. In addition, the labels are marked to the right of the figure. For Figure 1A, we have now indicated in the legend that all scale bars = 10 µm. In figure 3, neurons were co-transfected with GFP or GFP-Rab27b. Thus, the yellow signal in these images is the merge of the mCherry filler with either GFP (expression throughout the neuron body and dendrites) or GFP-Rab27b (punctate colocalization). We have added a scale bar to Fig 3A. Figure 6D has been corrected, with a “D” label added. Figure 4D shows representative images of cells with filopodia under the various conditions, including add-back of control or endoglin-KD EVs. We have clarified the conditions in the figure legend for 4D. For Figure 8, we have now split it into 2 figures: one with data (Fig 8) and one with the model (Fig 9).

      Reviewer #2 (Recommendations for the authors):

      For the most part, this story is strong and well-presented. The findings are interesting and will significantly advance our understanding of how EVs affect various processes such as cancer metastasis. However, the Cdc42 work is not great. They only indirectly implicate Cdc42 with a somewhat iffy inhibitor (ML141) and a constitutively active form transfected into cells. Both approaches have drawbacks such as off-target effects in the case of the inhibitor and possible cross-talk to other GTPases in the case of the active mutant. The activation of Cdc42 should be demonstrated by an activity assay. Several commercial kits are available. Inhibition of Cdc42 should be tested by knockdown in addition to the inhibitor.

      We appreciate the reviewer’s recognition of our work. To address the limitations of our study, particularly the Cdc42 mechanistic work, we have now added a “Limitations of the study” section at the end of the text. Here, we address our experimental limitations and future directions.

      Reviewer #3 (Recommendations for the authors):

      (1) Since the purified small EVs contain canonical exosomal markers and originate from MVEs, the authors should consider a more consistent use of the term "exosome" to avoid confusion.

      We acknowledge that the usage of both “exosomes” and “small extracellular vesicles” can seem confusing to many readers. Typically in the EV field, we use the term “exosome” when we can reliably determine that the EVs originate from the endocytic pathway. Thus, we use this term when we have specifically perturbed this pathway by targeting Hrs or Rab27. We use the term “small extracellular vesicles” or SEVs when referring to a purified heterogeneous population of SEVs from unknown or a variety of origins. Thus, when referring to vesicles isolated from the conditioned media, we call them SEVs because we cannot determine their origin. Clarification of this terminology has been added to the introduction of the paper.

      (2) 1st results section - expressing mCherry as a "filler" is confusing, clarify that this is meant to identify cellular background.

      This has now been clarified in the paper.

      (3) Figure 3 - Although Rab27a and Rab27b play a role in exosome secretion, Rab27b does not have redundant functions with Rab27a in every cellular context. The authors should mention the specific roles of Rab27a and Rab27b in promoting MVE fusion with the PM and in regulating the anterograde movement of MVEs to the PM, respectively (Ostrowski et al. 2010, Citation 52 in the ms). Although Rab27a is not highly expressed in neurons, it is not currently clear whether Rab27b has a redundant function with Rab27a or whether there is another unknown factor that plays this role. As neurons also do not express endoglin, the mechanisms that mediate how EVs regulate filopodia formation in these cells are most probably different than in cancer cells. This should be highlighted in the discussion.

      We have now added a couple of clarifying sentences about the roles of Rab27a and Rab27b to the results section, including the Ostrowski reference and another reference suggesting possible redundancy of Rab27a and Rab27b. With regard to endoglin not being expressed by neurons, that is one reason why we carried out the proteomics with control and endoglin-KD EVs to find a universal cargo that would directly induce filopodia formation. Indeed, THSD7A seems to be such a universal cargo, expressed in both cancer cell and neuron EVs and inducing filopodia in both cell types. This point, along with the requirement for regulation of THSD7A by other molecules in neurons, is discussed in the results and discussion sections.

      (4) As the authors note, the mechanistic link between endoglin-sorted, exosomal THSD7A and Cdc42-mediated filopodia formation remains unclear. While the findings on Cdc-42 are clear, they are not surprising. What is the role of mDia/ENA/VASP or BAR proteins in this? The authors should also consider an assay to determine whether exosomal THSD7A binds to the PM to cause the signaling or if the cargo is first internalized before performing its function. Since this process is both autocrine and paracrine, the authors could co-culture THSD7A-mScarlet cells with vector control cells and observe how THSD7A-mScarlet is localized in the non-expressing cells.

      As other reviewers also noted, the Cdc42 mechanistic data at the end of the paper has clear limitations that are now addressed within the manuscript in a “Limitations of the Study” section. Here we discuss our experimental troubleshooting and approach to assaying Cdc42 involvement in this process. We acknowledge there are many rigorous experiments that could be pursued in the future to strengthen our mechanism and proposed model.

      We also agree that elucidating how THSD7A specifically interacts with target cells would be very informative and insightful. This would be most effectively assayed using a cell line that is stably expressing THSD7A-mScarlet and could be a future direction of this project. However, it is out of the scope of this current publication.

    1. Author response:

      The following is the authors’ response to the original reviews

      Public Reviews:

      Reviewer #1 (Public review):

      In this study, Hama et al. explored the molecular regulatory mechanisms underlying the formation of the ULK1 complex. By employing the AlphaFold structural prediction tool, they showed notable differences in the complex formation mechanisms between ULK1 in mammalian cells and Atg1 in yeast cells. Their findings revealed that in mammalian cells, ULK1, ATG13, and FIP200 form a complex with a stoichiometry of 1:1:2. These predicted interaction regions were validated through both in vivo and in vitro assays, enhancing our understanding of the molecular mechanisms governing ULK1 complex formation in mammalian cells. Importantly, they identified a direct interaction between ULK1 and FIP200, which is crucial for autophagy. However, some aspects of this manuscript require further clarification, validation, and correction by the authors.

      Thank you for your thorough evaluation of our manuscript. We have carefully revised the manuscript to address your concerns by performing extra experiments and providing additional clarifications, validations, and corrections as written below.

      Reviewer #2 (Public review):

      Summary:

      This is important work that helps to uncover how the process of autophagy is initiated - via structural analyses of the initiating ULK1 complex. High-resolution structural details and a mechanistic insight of this complex have been lacking and understanding how it assembles and functions is a major goal of a field that impacts many aspects of cell and disease biology. While we know components of the ULK1 complex are essential for autophagy, how they physically interact is far from clear. The work presented makes use of AlphaFold2 to structurally predict interaction sites between the different subunits of the ULK1 complex (namely ULK1, ATG13, and FIP200). Importantly, the authors go on to experimentally validate that these predicted sites are critical for complex formation by using site-directed mutagenesis and then go on to show that the three-way interaction between these components is necessary to induce autophagy in cells.

      Strengths:

      The data are very clear. Each binding interface of ATG13 (ATG13 with FIP300/ATG13 with ULK1) is confirmed biochemically with ITC and IP experiments from cells. Likewise, IP experiments with ULK1 and FIP200 also validate interaction domains. A real strength of the work in in their analyses of the consequences of disrupting ATG13's interactions in cells. The authors make CRISPR KI mutations of the binding interface point mutants. This is not a trivial task and is the best approach as everything is monitored under endogenous conditions. Using these cells the authors show that ATG13's ability to interact with both ULK1 and FIP200 is essential for a full autophagy response.

      Thank you for your thoughtful review and for highlighting the importance of our approach.

      Weaknesses:

      I think a main weakness here is the failure to acknowledge and compare results with an earlier preprint that shows essentially the same thing (https://doi.org/10.1101/2023.06.01.543278). Arguably this earlier work is much stronger from a structural point of view as it relies not only on AlphaFold2 but also actual experimental structural determinations (and takes the mechanisms of autophagy activation further by providing evidence for a super complex between the ULK1 and VPS34 complexes). That is not to say that this work is not important, as in the least it independently helps to build a consensus for ULK1 complex structure. Another weakness is that the downstream "functional" consequences of disrupting the ULK1 complex are only minimally addressed. The authors perform a Halotag-LC3 autophagy assay, which essentially monitors the endpoint of the process. There are a lot of steps in between, knowledge of which could help with mechanistic understanding. Not in the least is the kinase activity of ULK1 - how is this altered by disrupting its interactions with ATG13 and/or FIP200?

      Thank you for this valuable feedback. In response, we performed a detailed structural comparison between the cryo-EM structure reported in the referenced preprint and our AlphaFold-based model. We have summarized both the similarities and differences in newly included figures (revised Figure 2A, B, 3B, S1F) and provided an in-depth discussion in the main text. Furthermore, to address the downstream consequences of ULK1 complex disruption, we have investigated the impact on ULK1 kinase activity, specifically examining how mutations affecting ATG13 or FIP200 interaction alter ULK1’s phosphorylation of a key substrate ATG14. In addition, we analyzed the effect on ATG9 vesicle recruitment. We provide the corresponding data as Figure S3C-E and detailed discussions in the revised manuscript.

      Reviewer #3 (Public review):

      In this study, the authors employed the protein complex structure prediction tool AlphaFold-Multimer to obtain a predicted structure of the protein complex composed of ULK1-ATG13-FIP200 and validated the structure using mutational analysis. This complex plays a central role in the initiation of autophagy in mammals. Previous attempts at resolving its structure have failed to obtain high-resolution structures that can reveal atomic details of the interactions within the complex. The results obtained in this study reveal extensive binary interactions between ULK1 and ATG13, between ULK1 and FIP200, and between ATG13 and FIP200, and pinpoint the critical residues at each interaction interface. Mutating these critical residues led to the loss of binary interactions. Interestingly, the authors showed that the ATG13-ULK1 interaction and the ATG13-FIP200 interaction are partially redundant for maintaining the complex.

      We are grateful for your high evaluation of our work.

      The experimental data presented by the authors are of high quality and convincing. However, given the core importance of the AlphaFold-Multimer prediction for this study, I recommend the authors improve the presentation and documentation related to the prediction, including the following:

      (1) I suggest the authors consider depositing the predicted structure to a database (e.g. ModelArchive) so that it can be accessed by the readers.

      We have deposited the AlphaFold model to ModelArchive with the accession code ma-jz53c, which is indicated in the revised manuscript.

      (2) I suggest the authors provide more details on the prediction, including explaining why they chose to use the 1:1:2 stoichiometry for ULK1-ATG13-FIP200 and whether they have tried other stoichiometries, and explaining why they chose to use the specific fragments of the three proteins and whether they have used other fragments.

      We appreciate your suggestion. As we noted in the original manuscript, previous studies have shown that the C-terminal region of ULK1 and the C-terminal intrinsically disordered region of ATG13 bind to the N-terminal region of the FIP200 homodimer (Alers, Loffler et al., 2011; Ganley, Lam du et al., 2009; Hieke, Loffler et al., 2015; Hosokawa, Hara et al., 2009; Jung, Jun et al., 2009; Papinski and Kraft, 2016; Wallot-Hieke, Verma et al., 2018). We relied on these findings when determining the specific regions to include in our complex prediction and when selecting a 1:1:2 stoichiometry for ULK1–ATG13–FIP200 which was reported previously (Shi et al., 2020). We also used AlphaFold2 to predict the structures of the full-length ULK1–ATG13 complex and the complex of the FIP200N dimer with full-length ATG13, confirming that there were no issues with our choice of regions (revised Figure S1A-C). In the revised manuscript, we have provided a more detailed explanation of our rationale based on the previous reports and additional AlphaFold predictions.

      (3) I suggest the authors present the PAE plot generated by AlphaFold-Multimer in Figure S1. The PAE plot provides valuable information on the prediction.

      We provided the PAE plot in the revised Figure S1C.

      Recommendations for the authors:

      Reviewer #1 (Recommendations for the authors):

      (1) In Figure 1D, the labels for the input and IP of ATG13-FLAG should be corrected to ATG13-FLAG FIP3A.

      We thank the reviewer for pointing out these labeling mistakes. We revised the labels based on the suggestions.

      (2) In the discussion section, the authors should address why ATG13-FLAG ULK1 2A in Fig. 2D leads to a significantly lower expression of ULK1 and provide possible explanations for this observation.

      ATG13 and ATG101, both core components of the ULK1 complex, are known to stabilize each other through their mutual interaction. Loss or reduction of one protein typically leads to the destabilization of the other. In this context, ULK1 is similarly stabilized by binding to ATG13. Therefore, ATG13-FLAG ULK2A mutant, which has reduced binding to ULK1, likely loses this stabilizing activity and ULK1 becomes destabilized, resulting in the lower expression levels of ULK1. We added these discussions in the revised manuscript.

      (3) In Figure 4B, the authors should explain why Atg13-FLAG KI significantly affects the expression of endogenous ULK1. Could Atg13-FLAG KI be interfering with its binding to ULK1? Experimental evidence should be provided to support this. Additionally, does Atg13-FLAG KI affect autophagy? Wild-type HeLa cells should be included as a control in Figure 4C and 4D to address this question.

      Thank you for your constructive suggestion. We found a technical error in the ULK1 blot of Figure 4B. Therefore, we repeated the experiment. The results show that ULK1 expression did not significantly change in the ATG13-FLAG KI. These findings are consistent with Figure S3A. We have replaced Figure 4B with this new data.

      We agree that including wild-type HeLa cells as a control is essential to determine whether ATG13-FLAG KI affects autophagy. We performed the same experiments in wild-type HeLa cells and found that ATG13-FLAG KI does not significantly impact autophagic flux. Accordingly, we have replaced Figures 4D and 4E with these new data.

      (4) In Figure 3C, the authors used an in vitro GST pulldown assay to detect a direct interaction between ULK1 and FIP200, which was also confirmed in Figure 3E. However, since FLAG-ULK1 FIP2A affects its binding with ATG13 (Fig. 3E), it is possible that ULK1 FIP2A inhibits autophagy by disrupting this interaction. The authors should therefore use an in vitro GST pulldown assay to determine whether GST-ULK1 FIP2A affects its binding with ATG13. Additionally, the authors should investigate whether the interaction between ULK1 and FIP200 in cells requires the involvement of ATG13 by using ATG13 knockout cells to confirm if the ULK1-FIP200 interaction is affected in the absence of ATG13.

      Thank you for the valuable suggestion. We examined the effect of the FIP2A mutation on the ULK1–ATG13 interaction using isothermal titration calorimetry (ITC) to obtain quantitative binding data. The results showed that the FIP2A mutation does not markedly alter the affinity between ULK1 and ATG13 (revised Figure S2B), suggesting that FIP2A mainly weakens the ULK1–FIP200 interaction. Regarding experiments in ATG13 knockout cells, ULK1 becomes destabilized in the absence of ATG13, making it technically difficult to assess how the ULK1–FIP200 interaction is affected under those conditions.

      Reviewer #2 (Recommendations for the authors):

      I feel the manuscript would benefit from a more detailed comparison with the Hurely lab paper - are the structural binding interfaces the same, or are there differences?

      We appreciate the suggestion to compare our results more closely with the work from the Hurley lab. We performed a detailed structural comparison between the cryo-EM structure reported in the referenced preprint and our AlphaFold-based model (revised Figure 2A, B, 3B, S1F) and provided an in-depth discussion in the main text.

      As mentioned, what happens downstream of disrupting the ULK1 complex? How is ULK1 activity changed, both in vitro and in cells? Does disruption of the ULK1 complex binding sites impair VPS34 activity in cells (for example by looking at PtdIns3P levels/staining)?

      Thank you for your insightful comments. We focused on elucidating how disrupting the ULK1 complex leads to impaired autophagy. To assess ULK1 activity, we measured ULK1-dependent phosphorylation of ATG14 at Ser29 (PMID: 27046250; PMID: 27938392). In FIP3A and FU5A knock-in cells, ATG14 phosphorylation was significantly reduced, indicating decreased ULK1 activity (revised Figure S3D, E). This observation is consistent with previous work showing that FIP200 recruits the PI3K complex. Notably, in ATG13 knockout cells, ATG14 phosphorylation became almost undetectable, though the underlying mechanism remains to be fully investigated. Altogether, these data point to reduced ULK1 activity as a key factor explaining the autophagy deficiency observed in FU5A knock-in cells.

      We also explored possible downstream mechanisms. One well-established function of ATG13 is to recruit ATG9 vesicles (PMID: 36791199). These vesicles serve as an upstream platform for the PI3K complex, providing the substrate for phosphoinositide generation (PMID: 38342428). To clarify how our mutations impact this step, we starved ATG13-FLAG knock-in cells and observed ATG9 localization. Unexpectedly, even in FU5A knock-in cells where ATG13 is almost completely dissociated from the ULK1 complex, ATG9A still colocalized with FIP200 (revised Figure S3C). These puncta also overlapped with p62, likely because p62 bodies recruit both FIP200 and ATG9 vesicles. Although we suspect that ATG9 recruitment is nonetheless impaired under these conditions, we were unable to definitively demonstrate this experimentally and consider it an important avenue for future study.

      Reviewer #3 (Recommendations for the authors):

      Here are some additional minor suggestions:

      (1) The UBL domains are only mentioned in the abstract but not anywhere else in the manuscript. I suggest the authors add descriptions related to the UBL domains in the Results section.

      We thank the reviewer for pointing out the lack of description of UBL domains, which we added in Results in the revised manuscript.

      (2) The authors may want to consider adding a diagram in Figure 1A to show the domain organization of the three full-length proteins and the ranges of the three fragments in the predicted structure.

      We have added a proposed diagram as Figure 1A.

      (3) I suggest the authors consider highlighting in Figure 1A the positions of the binding sites shown in Figure 1B, for example, by adding arrows in Figure 1A.

      We have added arrows in the revised Figure 1B (which was Figure 1A in the original submission).

      (4) In Figure 1D, "Atg13-FLAG" should be "Atg13-FLAG FIP3A".

      We have revised the labeling in Figure 1D.

      (5) "the binding of ATG13 and ULK1 to the FIP200 dimer one by one" may need to be re-phrased. "One by one" conveys a meaning of "sequential", which is probably not what the authors meant to say.

      We have revised the sentence as “the binding of one molecule each of ATG13 and ULK1 to the FIP200 dimer”.

      (6) In "Wide interactions were predicted between the four molecules", I suggest changing "wide" to "extensive".

      We have changed “wide” to “extensive” in the revised manuscript.

      (7) In "which revealed that the tandem two microtubule-interacting and transport (MIT) domains in Atg1 bind to the tandem two MIT interacting motifs (MIMs) of ATG13", I suggest changing the two occurrences of "tandem two" to "two tandem" or simply "tandem".

      We simply used "tandem" in the revised manuscript.

    1. 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

      General Statements

      We sincerely thank all three reviewers for their thoughtful and constructive feedback. Your comments were invaluable in improving the clarity and quality of our work.

      In this study, we revisit a previously overlooked lipophilic dye, demonstrating its utility for live-cell imaging that transport in a non-vesicular pathway and label autophagy related structures. Against the backdrop of increasing attention to membrane contact sites (MCSs), bridge-like lipid transfer proteins (BLTPs), and organelle biogenesis, we aim to propose the possibility of a reversible one-way phospholipid transfer activity that really takes place in living cells.

      As Reviewer #1 noted, recent cryo-EM studies (e.g., Oikawa et al.) have highlighted the importance of lipids in autophagosome formation. And there are some existed in vitro studies. However, we believe that we have to think about the consistence of simplified in vitro reconstitution and the complex real cellular environment. In addition, to our knowledge, no studies have directly tracked lipid flow dynamics over time in living cells. We believe our work contributes to this gap by combining three interesting technical approaches: (a) R18 as a lipid-tracing dye, (b) FRAP analysis on the isolation membrane, and (c) the use of Ape1 overexpression to stall autophagosome closure, enabling us to visualize reversible lipid flow in vivo. While these techniques may not appear "fancy," we hope they offer new insights that can inspire further exploration in lipid dynamics story in a real cellular environment.

      We appreciate Reviewer #2's comments on our high imaging quality and Reviewer #3's recognition of our approach as an elegant way to study lipid transfer. We have revised the manuscript accordingly and included additional explanations, figure clarifications, and planned experiments to address remaining concerns.

      As two key concerns were raised repeatedly by all reviewers, we would like to address them here:

      1. Regarding the concern that the evidence for reversible lipid transfer from the IM to the ER is not sufficiently strong:

      We are deeply grateful to Reviewer #2 for the insightful suggestion to compare the fluorescence recovery of the adjacent bleached ER to that of the ER-IM MCS, to exclude the possibility that recovery at the ER-IM MCS originates from nearby ER rather than from the IM. Following this suggestion, we performed a quantitative analysis using unbleached ER as a background. Interestingly, in every sample, the adjacent bleached ER consistently showed a significantly lower fluorescence recovery than the ER-IM MCS. We also used the IM as a background for normalization, the difference became even more pronounced, further supporting the idea that the adjacent ER could not be the source of the recovery signal at the ER-IM MCS. These findings strengthen our conclusion that phospholipid recovery at the MCS could be derived from the IM. The updated analysis and corresponding figure panels (Figure 5K, 5L, and 5M), along with the relevant text (lines 384-396), have been revised accordingly.

      Regarding the concern that the evidence for R18 transfer via Atg2 as a bridge-like lipid transfer protein is not sufficiently direct:

      In addition to the evidence presented in this manuscript, we have now cited our parallel study currently under revision (Sakai et al., bioRxiv 2025.05.24.655882v1), where we provide direct evidence that Atg2 indeed functions as a bridge-like lipid transfer protein, rather than a shuttle. Importantly, we also show in that study that R18 transfer requires the bridge-like structure of Atg2. This new reference has been cited in the revised manuscript, and relevant textual explanations have been added to provide further support.

      We hope that the revisions and our revision plan can address the reviewers key concerns. Please find our detailed point-by-point responses below.

      Response to the Reviewer ____#____1

      In their study, Hao and colleagues exploited the fluorescent fatty acid R18 to follow phospholipid (PL) transfer in vivo from the endoplasmic reticulum to the IM during autophagosome formation. Although the results are interesting, especially the retrograde transport of PLs, based on the provided data, additional control experiments are needed to firmly support the conclusions.

      We sincerely thank the reviewer for the positive assessment and agree that additional controls are necessary to support our conclusion. Detailed responses and corresponding revisions are provided below.

      An additional point is that the authors also study the internalization of R18 into cells and found a role of lipid flippases and oxysterol binding proteins. While this information could be useful for researchers using this dye, these analyses/findings have no specific connection with the topic of the manuscript, i.e. the PL transfer during autophagosome formation. Therefore, they must be removed.

      We thank the reviewer for the thoughtful comment. We understand the concern that the R18 internalization analysis may appear peripheral to the manuscript's main focus on phospholipid transfer during autophagosome formation. However, we respectfully believe that this section is critical for establishing the mechanistic basis as this study represents the first detailed in vivo application of R18 for tracing lipid dynamics. We believe it is interesting that R18 entry is not due to chemically passive diffusion or non-specific adsorption, but occurs through a biologically regulated, non-vesicular lipid transport pathway. This mechanistic context underpins the reliability of using R18 to monitor ER-to-IM lipid transport in the autophagy pathway.

      To improve clarity and coherence, we have added explanatory text in the Introduction and at the start of the Results section to explicitly link the internalization assay to the subsequent autophagy-related experiments (line 94-98, 185-187). We hope this helps guide the reader through the rationale and relevance of this part of the study.

      Major points:

      1) In general, the quality of the microscopy images are quite poor and this make it difficult to assert some of the authors' conclusions.

      We thank the reviewer for the feedback. To better address this concern, we would appreciate clarification regarding which specific images or figure panels were found to be of low quality. Overall, we believe the microscopy data presented are of sufficient resolution and clarity to support our main conclusions, as also noted by Reviewer #2 ("the high-quality images and FRAP experiments").

      We acknowledge that certain phenomena-such as occasional R18 labeling of the vacuole-were not clearly explained in the original manuscript. We have now included additional clarification in the results section and mentioned this limitation in the discussion (lines 170-171, 436-438), along with a note on ongoing experiments to further investigate this point.

      2) It would be important to perform some lipidomics analysis to determine in which PLs and other lipids or lipid intermediates R18 is incorporated. First, it will be important to know which the major PL species are are labelled under the conditions of the experiments done in this study. Second, the authors assume that all the R18 is exclusively incorporated into PLs and this is what they follow in their in vivo experiments. What about acyl-CoA, which has been shown to be a key player in the IM elongation (Graef lab, Cell)?

      We thank the reviewer for raising this point. However, we believe this is based on a misunderstanding of the chemical nature of R18. R18 is not a free fatty acid analog and cannot be incorporated into phospholipids or acyl-CoA via metabolic pathways. Due to its chemical structure-a bulky rhodamine headgroup attached to a long alkyl chain-it cannot undergo enzymatic conjugation or incorporation into membrane lipids. This is why we did not pursue lipidomics analysis. Instead, we focused on characterizing the biological behavior of R18 through a range of live-cell assays, including temperature and ATP dependency, involvement of flippases, OSBP proteins, and Atg2, all of which support a regulated, non-vesicular lipid transport pathway. Additionally, the AF3 structural model presented in this study is consistent with this interpretation, showing no evidence of R18 forming chemical bonds with phospholipids.

      3) Figure 1A and 1B. The authors conclude that Atg2 is involved in the lipid transfer since R18 does not localize to the PAS/ARS in the atg2KO cells. However, another possible explanation is that in those cells the IM is not formed and does not expand, and con sequetly R18 is present in low amounts not detectable by fluorescence microscopy. To support their conclusion, the authors must assess PAS-labelling with R18 in cells lacking another ATG gene in which Atg2 is still recruited to the PAS.

      We thank the reviewer for this important suggestion. As noted, the absence of R18 at the PAS in atg2Δ cells may reflect a lack of membrane formation rather than impaired lipid transfer. However, in support of our interpretation, our previous work (Hirata E, Ohya Y, Suzuki K, 2017) has shown that R18 accumulates at PAS-like structures in delipidation mutants, where the IM fails to expand but Atg2 is still recruited (please refer to the attached revision plan for further details). This suggests that the presence of Atg2, rather than the mere existence of a mature IM, contributes to R18 localization.

      To address this, we revised our statement to the more cautious: "R18 was undetectable at the PAS in atg2Δ cells," to avoid overinterpretation (lines 119-120). 4)

      4) Figure 2. As written, the paragraph this figure seems to indicate that flippases are directly involved in the translocation of R18 from the PM to the ER. As correctly indicated by the authors, flippases flip PLs, not fatty acids. Moreover, there are no PL synthesizing at the PM and thus probably R18 is not flipped upon incorporation into PL. As a result, the relevance of flippase in R18 internalization is probably indirect. This must be explained clearly to avoid confusion/misunderstandings.

      We thank the reviewer for this important clarification. We fully agree that flippases act on phospholipids, not fatty acids, and that R18 is not metabolically incorporated into phospholipids at the plasma membrane. However, our ongoing work (Rev. Figure 1) shows that R18 preferential labeling affinity for PS and PE in vivo (yeast phospholipid synthesis mutants), consistent with its flippase-dependent localization. Flippases are known to specifically flip PS and PE. While R18 itself is not enzymatically modified or incorporated into phospholipids, its membrane distribution may thus depend on the lipid environment and the activity of lipid-translocating proteins.

      Preliminary data supporting this observation are included in the "Supplementary Figures for reviewer reference only" and are not part of the public submission.

      5) A couple of manuscript has shown a (partial) role of Drs2 in autophagy. The authors must explain the discrepancy between their own results and what published, especially because they use the GFP-Atg8 processing assay, which is less sensitive than the Pho8delta60 used in the other studies.

      We thank the reviewer for raising this important point. We are aware of prior reports implicating Drs2 in autophagy and in fact discussed this work directly with the authors during the course of our experiments, who kindly provided helpful suggestions. While our GFP-Atg8 processing assay did not show significant defects upon Drs2 deletion, strain background differences may explain this discrepancy. We also appreciate the suggestion to use the Pho8Δ60 assay and plan to include it in future experiments.

      Additionally, authors should check whether the Atg2 and Atg18 proteins are present at the IM-ER membrane contact sites in the same rates after nutrient replenished than when cells are nitrogen-starved, since this complex would determine the lipid transfer dynamics at this membrane contact site.

      We thank the reviewer for the helpful suggestion. We plan to perform additional experiments to monitor Atg18 localization during the nutrient replenishment assay.

      6) Authors used a predicted Atg2 lipid-transfer mutant (Srinivasan et al, J Cel Biol, 2024), but not direct prove that this mutant is defective for this activity. As previously done for other Atg2/ATG2-related manuscripts (Osawa et al, Nat Struct Mol Biol, 2019; Valverde et al, J Cel Biol, 2019), this must be measure in vitro. Moreover, they do not show whether other known functions of Atg2 are unaffected when expressing this Atg2 mutant, e.g. formation of the IM-ER MCSs, Atg2 interaction with Atg9 and localization at the extremity of the IM...

      We thank the reviewer for this concern. The lipid-transfer-deficient Atg2 mutant used here is based on the same structural rationale as in our recent parallel study (Sakai et al., bioRxiv 2025; https://www.biorxiv.org/content/10.1101/2025.05.24.655882v1, currently under revision). In that study, we addressed whether Atg2 indeed functions as a bridge-like lipid transfer protein, and also used R18 to directly demonstrate the lipid transfer defect of this Atg2 mutant in vivo.

      We therefore believe that referencing this study provides mechanistic support for the use of this Atg2 mutant in the current manuscript. A citation and brief explanation have now been added to the revised text (line 315-316, 439-441). We also plan to perform the lipid transfer assay in vitro.

      7) The mNG-Atg8 signal is not recovered in the fluorescent recovery assays. Based on the observation that R18 signal comes back after photobleaching, authors suggest that the supply of Atg8 is not required for IM expansion. This idea is opposite to data where the levels of Atg8 and deconjugation of lipidated Atg8 determines the size of the forming autophagosomes (e.g., Xie et al, Mol Biol Cell, 2008; Nair et al, Autophagy, 2012). Similar results have also been obtained in mammalian cells (Lazarou and Mizushima results in cell lacking components of the two ubiquitin-like conjugation systems). This discrepancy requires an explanation.

      We thank the reviewer for pointing out this imprecise interpretation, and we sincerely apologize for the confusion it may have caused. We fully agree that Atg8 is essential for the expansion of the isolation membrane (IM), as supported by previous studies. In our FRAP data, mNG-Atg8 showed gradual recovery at the later timepoints, indicating that Atg8 can be replenished over time. The reason why R18 recovery appears much more rapid is likely due to the inherently fast lipid transfer activity of Atg2, the bridge-like lipid transport protein. In contrast, Atg8 signal recovery may have been delayed for two reasons: (1) slower recruitment kinetics to the IM, and (2) partial depletion of the available mNG-Atg8 protein pool due to photobleaching during the experiment.

      We have revised the relevant paragraph in the manuscript (line 326-330) to clarify these points and avoid potential misinterpretation.

      8) Although authors claim that there is a retrograde lipid transfer from the IM to the ER, based on the data, it quite difficult to extract these conclusions as they show a decrease in the lipid flow dynamics rather to an inversion of the lipid flow per se. Can the authors exclude that ER microdomains are formed at the ERES in contact with the IM, and consequently what they measure is a slow diffusion of R18-labeled lipid from other part of the ER to these ERES?

      We appreciate the reviewer's insightful comment. Indeed, we are also considering the possibility that lipid-enriched microdomains may form in the ER and contribute to complex lipid dynamics at contact sites. However, direct visualization of such domains in cells remains technically challenging, this remains one of the important directions we aim to pursue in future studies. While our current data do not allow us to definitively state that all recovered lipids originate from the IM, our FRAP experiments provide indirect yet strong support for the possibility that at least a substantial portion of the recovered lipid signal in the ER derives from the IM. Moreover, following Reviewer 2's major point No.4, we performed a direct comparison of R18 fluorescence recovery between the photobleached ER-IM MCS region and the adjacent bleachedER region (Figure 5K and 5M). Interestingly, each sample consistently showed lower fluorescence recovery in the adjacent bleached ER near the ER-IM MCS (mean = 0.20), compared to the ER-IM MCS region (mean = 0.28). To further validate this observation, we also used the IM as a background reference for normalization. This analysis revealed a more significant difference, with the adjacent bleached ER near the ER-IM MCS showing a lower recovery (mean = 0.47) than the ER-IM MCS (mean = 0.80).

      As the Reviewer2 pointed out, these results support our reversible lipid transfer model by demonstrating that fluorescence recovery at the ER-IM MCS is due to the signal coming from the IM, rather than from the adjacent bleached ER, which recovers more slowly and less efficiently. We have incorporated this new analysis into Figure 5, and accordingly revised the figure legend and main text (lines 384-396).

      9) The retrograde PL transfer is studied in cells overexpressing Ape1, in which IM elongation is stalled. This is a non-physiological experimental setup and consequently it is unclear whether what observed applies to normal IM/autophagosomes. This event should be shown to occur in WT cells as well.

      We thank the reviewer for this point. Indeed, it remains technically difficult to visualize lipid flow during normal IM expansion in vivo, as this process is rapid and transient. And to date, there are no reports directly addressing lipid flow in this process.

      But the Ape1 overexpression system provides a strategic advantage by temporally extending the IM elongation phase and spatially enlarging the IM, thus offering a unique opportunity to capture membrane behavior that would otherwise be transient and difficult to resolve. Importantly, this system arrests autophagosome closure, which we leveraged to investigate the potential reversibility of phospholipid transfer in a controlled and prolonged context. Without this system, it would be exceedingly difficult for reaserchers to examine the lipid flow directionality in living cells.

      Furthermore, the use of Ape1 overexpression has been widely employed in previous high-impact autophagy studies. We emphasize that our aim is to understand Atg2-mediated lipid transfer, and in this context, the Ape1 system provides a valuable and informative tool without compromising the validity of our conclusions.

      10) From the images provided, it appears that R18 also labels the vacuole. The vacuole form MCSs with the IM. Can the author exclude a passage of R18 from the vacuole to the IM?

      We thank the reviewer for the insightful comment. Our data suggest that R18 traffics from the plasma membrane to the ER, then to autophagy-related structures. Actually, following that, as we kown, autophagosomes will eventually reaches and fused with the vacuole. This explains the occasional weak R18 signals at the vacuole membrane, particularly in late-stage cells. We have revised the figure and clarified this point in the text to avoid oversimplification of R18 localization (lines 169-171, 426-428)

      Here we also added the results of our onging work (in preparation). R18 tends to accumulate in a dot-like compartment after prolonged rapamycin treatment and incubation (Rev. Figure 2). And the vacuolar labeling of R18 correlates with the degradation status of autophagosomes, rather than reverse lipid transport from the vacuole to the IM (Rev. Figure 2). Taken together, we believe that R18 transport from the vacuole back to the IM is unlikely.

      Preliminary data supporting this response are included in the "Supplementary Figures for reviewer reference only" and are not part of the public submission.

      Minor points:

      1) L66. One report has indicated that Vps13 may also play a role in the transfer of lipids from the ER to the IM (Graef lab, J. Cell Biol).

      Thank you for pointing this out. Their excellent work also suggested that the inherent lipid transfer activity of Atg2 is required for IM expansion. We have revised the sentence (lines 67-68, 312-314) and included the appropriate citation at these two places.

      2) L70. It must be indicated that IM is also called phagophore.

      We have revised the sentence (line 70-71). Thank you for pointing this out.

      3) L74. It is mentioned "Additionally, a hydrophobic cavity in the N-terminal region of Atg2 directly tethers Atg2 to the ER, particularly the ER exit site (ERES), which is considered a key hub for autophagosome biogenesis", but there is no experimental evidence supporting that Atg2 is involved in the tethering with the ERES.

      Thank you for pointing this out. We have removed the N-terminal region part and revised the sentence accordingly (line 79-81) to avoid overstatement.

      4) L90. PAS must be listed between the ARS.

      We have revised the sentence (line 97-98). Thank you for pointing this out.

      5) Upon deletion of ATG39 and ATG40, there is a pronounced reduction of mNG-Atg8 labelled with R18. This would suggest that these two ER-phagy receptors are required for the PL transfer from the ER to the IM, which is not the case as autophagy is mildly affected by the absence of them (e.g., Zhang et al, Autophagy, 2020).

      We thank the reviewer for the important comment and agree that Atg39 and Atg40 are not required for phospholipid transfer from the ER to the IM. We have revised the text (lines 155-157). We appreciate if the reviewer could provide the DOI or PubMed ID for this paper.

      6) Authors referred that "no direct evidence has been found to confirm lipid transfer at the ER-IM MCS in living cells" (lines 282-283). However, a recent paper has shown that de novo-synthesized phosphatidylcholine is incorporated from the ER to the autophagosomes and autophagic bodies (Orii et al, J Cel Biol, 2021). This reference should be mentioned in the manuscript.

      Thank you for your insightful reminder. This paper beautifully demonstrated the importance of de novo-synthesized phosphatidylcholine in autophagy using electron microscopy. We have now included its citation and brief discussion in the revised manuscript (lines 74-76, 297-298). However, we respectfully note that direct observation of lipid transfer at the ER-IM MCS in living cells still remains unproven.

      7) In lines 252-253, the sentence "R18 transport from the PM to the ER was partially impaired in osh1Δ osh2Δ, osh6Δ osh7Δ, and oshΔ osh4-1 cells (Figure S3). These results suggest that Osh proteins participate in transferring R18 from the PM to the ER" does not recapitulate what is observed in Fig. S3. Moreover, the Emr lab has generate a tertadeletion mutant in which the PM-ER MCSs are abolished. The authors could examine this mutant.

      We thank the reviewer for this helpful comment and sincerely apologize for the lack of clarity in our original description. Our conclusion was primarily based on the partial PM accumulation of R18 observed in some osh mutant strains shown in Figure S3, which motivated us to further investigate this pathway using the OSW-1 inhibitor. We have revised the corresponding text to improve the logic and clarity of this section.

      We appreciate the recommendation of the tether∆ mutant. Our preliminary tests indicate that R18 still properly labels the ER in tether∆ cells, suggesting that its localization is not due to passive diffusion at membrane contact sites, but rather involves specific transport mechanisms. As this is an initial observation, we plan to confirm the result and include it in a future revision.

      Reviewer #1 (Significance (Required)):

      General assistent: Strength: potential new system to monitor lipid flow Limitations: Indirect evidences and in the case of the retrograde transport of phospholipids, it could be an artefact of the employed experimental approach. Advance: Little advances because something in part already shown in vitro. No new mechanisms uncovered. Audience: Autophagy and membrane contact site fields.

      We sincerely thank the reviewer for the overall evaluation. We agree that our current system offers indirect but promising evidence for lipid transfer events at ER-IM contact sites in vivo. While Atg2-mediated lipid transport has been proposed in vitro, our study adds value by (1) establishing a live-cell imaging way to monitor lipid flow in a non-vesicular transport pathway, (2) proposing a model of reversible one-way lipid transfer activity, and (3) addressing whether findings from simplified in vitro reconstitution accurately reflect the dynamics in the more complex real cellular environment.

      We recognize the limitations of our current approach and plan to include additional analyses to more cautiously interpret the observed retrograde movement. Although we do not claim to identify a new mechanism, we believe our work provides an interesting framework to inspire future efforts aimed at directly probing lipid flow at membrane contact sites in vivo.

      We also sincerely appreciate the reviewer's recognition of the potential value of this system for the autophagy and membrane contact site communities.

      Response to the Reviewer ____#2

      Non-vesicular lipid transfer plays an essential role in organelle biogenesis. Compared to vesicular lipid transfer, it is faster and more efficient to maintain proper lipid levels in organelles. In this study, Hao et al. introduced a high lipophilic dye octadecyl rhodamine B (R18), which specifically labels the ER structures and autophagy-related structures in yeast and mammalian cells. They characterised its distinct lipid entry into yeast cells via lipid flippase Neo1 and Drs2 on the plasma membrane, rather than through the endocytic pathway. They then demonstrated that R18 intracellular trafficking through plasma membrane to ER depends on "box-like" lipid transfer Osh proteins. They further looked into the "bridge-like" lipid transfer protein Atg2, using R18 as a lipid probe to track lipid transfer from ER to the isolation membrane (IM) during membrane expansion and reversible lipid transfer through IM to the ER-IM membrane contact sites (MCS) when autophagy is terminated by nutrient replenishment. The authors provide an interesting model of reversible directionality of Atg2 lipid transfer during autophagy induction and termination.

      We sincerely thank the reviewer for the thoughtful and constructive summary of our work. We are grateful for the recognition of the novelty of using R18 to visualize non-vesicular lipid transfer in vivo and for highlighting the conceptual contribution of our proposed model of reversible Atg2-mediated transport during autophagy.

      In response to the reviewer's valuable suggestions, we have revised key parts of the manuscript and prepared a detailed revision plan to address the specific concerns. We truly appreciate the reviewer's insights, which have been instrumental in improving the clarity of our study.

      Major points:

      1. Line 299-309: The FRAP assays were interesting and well performed. The authors photobleached R18 and Atg8 signal, and found R18 fluorescence recovery but not Atg8, which suggests lipid transfer occurs between ER and the IM and faster than Atg8 lipidation process during IM expansion. These results gave clear evidence that R18 can be transferred during IM expansion. The supply of Atg8 may not be not able to track within this time frame or the recovered amount of Atg8 may not be able to visualized due to the threshold limitation with confocal microcopy. This does not imply the supply of Atg8 to the IM is not required during IM expansion. This should be clarified.

      We thank the reviewer for this valuable comment and fully agree that Atg8 is essential for IM expansion. We apologize for any ambiguity that may have suggested otherwise.

      As pointed out, the lack of mNG-Atg8 recovery in our FRAP assay likely reflects the slower turnover of lipidated Atg8, limited observation time, and photobleaching of the existing protein pool. Notably, we observed a weak but gradual signal recovery at later time points, supporting this view. We have revised the relevant paragraph in the manuscript (line 326-330) to clarify these points and avoid potential misinterpretation.

      Please clarify how the length of the IM is measured and determined in Figure 4H and Figure 5D.

      We thank the reviewer for the vaulable comment. We have now clarified the method for quantifying IM length in the revised manuscript. Specifically, we modified the Statistical Analysis section of the Methods (line 642-643).

      Line 336-342: The description of the results should be clarified. Based on Figure 5H, the authors observed a significant decrease in the mNG-Atg8 signal during photobleaching of the R18 signal.

      We thank the reviewer for pointing out the ambiguity. We have now clarified the description in the revised manuscript. The sentence has been modified (line 360-362) as follows: "To determine whether nutrient replenishment terminates autophagy, we selectively photobleached the R18 signal and monitored the R18 (photobleached) and mNG-Atg8 (without photobleaching) signal following nutrient replenishment."

      The authors photobleached ER-IM MCS and the ER region (boxed region in Figure 5J) and quantified fluorescence recovery, normalized to the IM region and an ER control. The ER control was taken from the other cell. It would be helpful to compare and analyse the fluorescence recovery of R18 in the bleached ER region near the ER-IM MCS to that in the ER-IM MCS. This would help to confirm the ER-IM MCS fluorescence recovery is due to signal coming from the IM.

      We sincerely thank the reviewer for this insightful suggestion. We have now performed the suggested comparison. Interestingly, each sample consistently showed lower fluorescence recovery in the adjacent bleached ER near the ER-IM MCS (mean = 0.20), compared to the ER-IM MCS region (mean = 0.28). To further validate this observation, we also used the IM as a background reference for normalization. This analysis revealed a more significant difference, with the adjacent bleached ER near the ER-IM MCS showing a lower recovery (mean = 0.47) than the ER-IM MCS (mean = 0.80).

      As the reviewer pointed out, these results support our reversible lipid transfer model by demonstrating that fluorescence recovery at the ER-IM MCS is due to the signal coming from the IM, rather than from the adjacent bleached ER, which recovers more slowly and less efficiently. We have incorporated this new analysis into Figure 5, and accordingly revised the figure legend and main text (lines 384-396). Again, we appreciate this constructive and helpful suggestion.

      In figure 5K, the autophagic structure or IM labelled by R18 seems to be maintained when the mNG-Atg8 signal decreases or dissociates from the IM. Could the authors comment on that how they interpret the termination of the prolonged IM structure and IM shrinkage?

      We thank the reviewer for this insightful observation. Based on our live-cell imaging, we speculate that following the initial dissociation of Atg8, the IM membrane undergoes a relatively slow disassembly process, potentially retracting toward the ER-IM MCS, which often localizes near ER exit sites (ERES). This suggests that IM shrinkage may proceed via Atg8-independent mechanisms. Although the precise pathway remains unclear, we occasionally observed vesiculation events during this phase, supporting the idea that membrane remodeling continues even in the absence of Atg8. In response to this comment, we have revised our manuscript to reflect these interpretations (line 494-496).

      The author has shown that Atg2Δ and Atg2LT lipid transfer mutant impair R18 labelling of autophagic structures in Figure 4C. However, the evidence supporting that R18 fluorescence recovery at ER-IM MCS is mediated by reversible Atg2 lipid transfer is not direct. It would be helpful to clarify whether Atg2 stays on the enlarged autophagic membranes when the membrane has reached to its maximum length and no longer grows.

      We thank the reviewer for this important suggestion. As noted in our response to Reviewer 1 (Major Point 8-2), clarifying whether Atg2/Atg18 remains at the ER-IM contact sites after IM expansion is indeed important for supporting the reversible lipid transfer model. We plan to monitor the localization of Atg18 during the nutrient replenishment assay.

      Minor points:

      1. Figure 2A "Dpm-GFP" is missing. The experiment replicates in Figure 2M should be indicated.

      We thank the reviewer for pointing out these issues. The label for "Dpm-GFP" has been added in Figure 2A, and the number of experimental replicates for Figure 2M is now indicated in the figure legend.

      Figure S2, the magenta panel should be "R18".

      We thank the reviewer for catching this labeling error. We have corrected the magenta panel label in Figure S2 to "R18" in the revised version of the figure.

      Line 341-342: "Figure 5H and 5J" should be "Figure 5H and 5I"

      We thank the reviewer for pointing out this error. The citation has been corrected from "Figure 5H and 5J" to "Figure 5H and 5I" in the revised manuscript.

      Please describe how the lipid docking model of Atg2 is generated.

      We thank the reviewer for this question. We have added a description of the modeling approach in the Methods section of the revised manuscript (lines 640-646). We also added the configuration files of AlphaFold3 to the supplementary information.

      Reviewer #2 (Significance (Required)):

      Currently, lipid probes are emerging as powerful tools to understand membrane dynamics, integrity, and the lipid-mediated cellular functions. In this manuscript, the authors performed a detailed characterisation of octadecyl rhodamine B (R18) as a potential lipid probe, which specifically labels ER and autophagic membranes. They present high quality imaging data and performed FRAP experiments to monitor the membrane dynamics and investigate the lipid transfer directionality between the ER and autophagic structure. However, the evidence of Atg2-mediated reversible lipid transfer may not be direct and sufficient. The proposed reversible lipid transfer model is interesting and provides an explanation of lipid level regulation during autophagosome formation.

      We sincerely thank the reviewer for the positive assessment of our work and for acknowledging the potential of R18 as a lipid probe, as well as the quality of our imaging and FRAP experiments. We are particularly grateful that the reviewer found the proposed model of reversible lipid transfer both interesting and relevant to the broader question of lipid regulation during autophagosome formation.

      Regarding the reviewer's concern that the evidence for Atg2-mediated reversible lipid transfer may not be sufficiently direct, we agree this is a critical point. While technical limitations currently prevent direct visualization of lipid flow reversal at single-molecule resolution in vivo, we hope our revision plan strengthen the proposed model and better convey its biological relevance, while also acknowledging the current limitations and the need for further mechanistic work.

      Response to the ____Reviewer #3

      The authors address the question of how autophagic membrane seeds expand into autophagosomes. After nucleation, IMs expand in dependence of the bridge-like lipid transfer protein Atg2, which has been shown to tether the IM to the ER. Several studies have shown in vitro evidence for direct lipid transfer by Atg2 between tethered membranes, and previous evidence has shown that the hydrophobic groove of Atg2 implicated in lipid transfer is required for autophagosome biogenesis in vivo in yeast and mammalian cells.

      In this manuscript, the authors take advantage of the dye R18, which they show accumulates mainly in the ER after a few minutes. They show specifically that the import of R18 into cells and transfer to the ER depends on the activity of flippases in the plasma membrane and OSPB-related lipid transporter. Using different sets of FRAT experiments, the authors track the fluorescence recovery of R18 in the IM, the IM-ER membrane contact site and the neighboring ER. From these experiments the authors conclude that (a) R18 is transferred to IM from the ER when IMs expand and (b) can be transferred from IMs back to the ER when autophagy is deactivated.

      The use of a lipophilic dye to monitor lipid dynamics during IM expansion or dissolution is an elegant way to probe the mechanisms of lipid transfer across ER-IM contact sites. Quantitative in vivo data is critically needed to address this fundamental question in autophagy and contact site biology. However, the study remains limited in providing direct evidence that it is indeed the lipid transfer activity of Atg2, which underlies the R18 dynamics in IMs in vivo.

      We sincerely thank the reviewer for this thoughtful and encouraging summary. We appreciate the recognition of our approach using R18 to visualize lipid dynamics at ER-IM contact sites, and agree that in vivo quantitative data are critically needed to advance our understanding of autophagic membrane expansion.

      We also fully agree with the reviewer that our current study provides indirect-but conceptually informative-support for Atg2-mediated reversible one way lipid transfer. While prior in vitro studies have demonstrated the lipid transfer capability of Atg2, our goal here was to develop a live-cell system that allows the dynamic tracking of lipid flow in vivo, and to explore the possibility of reversible transport during autophagy termination. We hope our story will offer unique insights for future studies aiming to directly probe lipid transfer mechanisms in live cells.

      Regarding the reviewer's concern about the lack of direct evidence that Atg2's lipid transfer activity underlies the observed R18 dynamics, we fully acknowledge this limitation. To address this point, we would like to cite our parallel study currently under revision (Sakai et al., bioRxiv 2025.05.24.655882v1), which provides additional mechanistic evidence linking R18 dynamics to the lipid transfer function of Atg2. Further details and planned revisions are described in the responses below.

      Major points:

      (1) The authors use R18in FRAP experiments to follow its transfer from the ER into IMs. However, whether this transfer is mediated by Atg2 via its inherent lipid transfer activity remains indirect. The only evidence that implicates Atg2 directly is the observation that a lipid transfer deficient Atg2 variant fails to support IM expansion and autophagosome biogenesis. A similar full-length Atg2 mutant has previously been shown to block autophagosome formation in Dabrowski et al. 2023 in yeast, which the authors do not cite or discuss, suggesting the inherent lipid transfer activity of Atg2 is required for IM expansion. However, aside from this experiment, the mechanisms underlying R18 transfer remain unclear and, while they likely depend on or are at least partially mediated by Atg2, they may involve alternative mechanisms including vesicle transport or continuous membrane contacts. Moreover, for the assays with stalled or dissolving IM, it is essential for the authors to test whether Atg2 is still associated with these IMs. It is quite possible that Atg2 dissociates from maximally expanded or dissolving IMs, which would make their interpretation of the data very unlikely. Thus, it will be critical to provide consistent evidence that lipid transfer from the IM to the ER is mediated by Atg2. Ideally, the authors would label IM with BFP-Atg8, R18, and Atg2-GFP and perform their in vivo analysis.

      We sincerely thank the reviewer for the critical comments and valuable suggestions. To further support the link between R18 transfer and Atg2, we would like to highlight two complementary findings. As noted in our response to Reviewer 1 (Major Point 3), R18 can still label the PAS even when Atg2 is recruited but IM expansion is impaired, suggesting that R18 trafficking occurs in an Atg2-dependent manner. In addition, in our parallel study (bioRxiv, 2025.05.24.655882v1), we demonstrated that Atg2 acts as a bridge-like lipid transfer protein. Notably, when we mutated the bridge-forming region of Atg2, R18 transport to the IM was also disrupted.

      We greatly appreciate the reviewer's reminder regarding the study by Dabrowski et al., 2023, which we have now cited and discussed in the revised manuscript (lines 66-68, 312-314). Their findings that the inherent lipid transfer activity of Atg2 is required for autophagosome formation in vivo strongly reinforce our model.

      Regarding the possibility of vesicle transport, we consider this contribution minimal based on R18's preferential labeling of continuous membranes and its divergence from FM4-64 staining. As for the role of continuous membrane contacts, as also mentioned in our response to Reviewer 1, our preliminary tests indicate that R18 still properly labels the ER in tether∆ cells, suggesting that its localization is not due to passive diffusion at membrane contact sites, but rather involves specific transport mechanisms. As this is an initial observation, we plan to confirm the result and include it in a future revision.

      We also thank the reviewer for the suggestion to monitor Atg2 localization at the dissolving IM. As similarly pointed out by two other reviewers, we plan to track Atg18 during the nutrient replenishment assay.

      Finally, we appreciate the idea of triple-labeling with BFP-Atg8, R18, and Atg2-GFP. While our preliminary attempts encountered technical difficulties such as abnormal BFP-Atg8 localization and severe bleaching during long-term imaging in yeast, we plan to optimize this approach in future experiments.

      (2) Given the ER forms contact sites with many organelles using bridge-like lipid transfer proteins, how do the authors explain the preferential accumulation of R18 in ARS and not in for example PM (Fmp27), mitochondria, endosomes or vacuole (Vps13)? Why should R18 specifically transferred by Atg2 and not or to a much lower rate by Fmp27 or Vps13?

      We sincerely thank the reviewer for raising this insightful question. Indeed, we have carefully considered this point. Our data indicate that R18 labeling of autophagy-related structures (ARS) depends on Atg2, as demonstrated in the present manuscript and supported by our parallel study currently under revision (bioRxiv, 2025.05.24.655882v1).

      We speculate that the preferential accumulation of R18 in ARS may arise from structural and contextual differences among bridge-like LTPs, such as Atg2, Vps13, and Fmp27. Although all are capable of mediating lipid transfer, these proteins differ in their membrane tethering modes, cargo specificity, and spatial regulation. For example, Atg2 localizes specifically to ER-IM contact sites during autophagosome formation, where membrane expansion requires rapid lipid supply. In contrast, Vps13 and Fmp27 may function at more stable or less dynamic contacts, where lipid turnover or probe accessibility is more limited. We have added a brief discussion of this point in the revised manuscript to reflect this important consideration (lines 439-444).

      (3) Does R18 label autophagic bodies after they are formed. Could the authors add R18 after autophagic bodies have formed in atg15 or pep4 cells?

      We thank the reviewer for this excellent suggestion. To address whether R18 can label autophagic bodies post-formation, we plan to perform additional experiments by adding R18 after autophagic bodies have accumulated in atg15Δ or pep4Δ cells. This will help clarify whether R18 incorporates into pre-formed autophagic bodies or requires earlier membrane dynamics for its labeling.

      (4) Since Neo1- or OSBP-defective cells do not transfer R18 from the PM to the ER or other membranes, the authors should include these strains as controls for ER-dependent R18 transfer to ARSs.

      We thank the reviewer for this insightful suggestion. To further validate the ER-dependency of R18 transfer to autophagy-related structures, we plan to include Neo1- and OSBP-deficient strains as additional controls.

      Comments:

      The authors neglect to mention or discuss important recent literature directly related to their study:

      Schutter et al., Cell (2020); Orii et al., JCB (2021); Polyansky et al., EMBOJ (2022); Dabrowski et al., JCB (2023); Shatz et al., Dev Cell (2024)

      We sincerely thank the reviewer for pointing out these important and highly relevant studies. We apologize for our oversight in not citing them earlier. Each of these works has provided valuable insights that are directly related to and have greatly informed our current study. We have now cited and discussed these references in appropriate sections of the revised manuscript.

      Figure 1A and B: The authors need to describe how these cells were stained with R18 in the figure legend or text to help the reader to understand how these experiments were performed. Figure legends need to indicate at which time point after rapamycin treatment cells were analyzed.

      Thank you for the helpful suggestion. We have now added the corresponding information to the figure legends to clarify the staining procedure and time points.

      The authors need to clarify whether mNG-Atg8 colocalization with R18 was included for dot- and ring-like structures for WT cells as shown separately in 1A but not in 1B.

      Thank you for the comment. The quantification in Figure 1B includes both dot- and ring-like structures of mNG-Atg8 colocalized with R18 in WT cells, as shown in Figure 1A. We have now clarified this point in the revised figure legend.

      Figure 1C: The figure legend needs to describe the conditions cells were treated with and when cells were analyzed after rapamycin treatment (presumably).

      Thank you for the helpful suggestion. We have now added the corresponding information to the figure legends.

      Figure 1C: The authors should combine atg15 and pep4 deletions with atg2 or atg7 as controls in which autophagic bodies are not formed.

      Thank you for the valuable suggestion. We plan to perform these experiments that combine atg15 and pep4 deletions with atg2 or atg7 as controls.

      Figure 1E and F: R18 stains more than just the ER in the cells shown. In addition to atg39 and atg40, authors should include atg11 to inhibit all forms of selective autophagy.

      Thank you very much for the insightful comment. We agree and plan to include the atg11Δ mutant to inhibit all forms of selective autophagy.

      Figure S2A and B: The figures are mislabeled. Instead of FM4-64 it should say R18. In addition to the ER, in several images it is obvious to see R18 staining the vacuole membrane (for example Figure 2A 30 degrees) and others. Thus, the strong thresholding in S2 may give the reader an oversimplified view on R18 localization. This needs to be corrected.

      Thank you very much for pointing this out. We have corrected the labeling error in Figure S2A and B. Regarding the observation that R18 occasionally labels the vacuole membrane, we agree with the reviewer's comment. Based on our data, we believe that this signal likely reflects autophagosomes that have reached and fused with the vacuole, as expected in the later stages of autophagy. We have clarified this point in the text to avoid oversimplification of R18 localization (lines 169-171, 426-428).

      Figure 1G and H: In 1G, there are number of R18-stained patches not co-labeled by GFP-ER. What are these patches and which organelles to they represent? In 1H, given the tight association of the ER (omegasome) with forming IMs, it is difficult to discern whether R18 labels surrounding ER membrane or the IM itself. This needs to be more closely analyzed. The authors need to quantify these data similar to the yeast data.

      Thank you for the suggestion. We plan to perform additional quantification and colocalization analysis to clarify the identity of R18-positive signals in 1G and 1H.

      Figure 4A-C: A full-length PLT-deficient variant of Atg2 has been analyzed by Dabrowski et al, JCB 2023 in vivo. This work needs to be cited and discussed. The analysis needs to include punctate Atg8 structures for WT cells to exclude effects due to expansion defects.

      Thank you for the suggestion. We have now cited and discussed the work by Dabrowski et al., JCB 2023 in the revised manuscript (lines 67-68, 312-314). In addition, we have included an analysis of punctate Atg8 structures in WT cells to address the concern regarding potential expansion defects.

      Figure 4F-H: To measure the size changes in IMs, the authors would need to perform these experiments without bleaching the mNG-Atg8 signals.

      We apologize for the lack of clarity. The method for measuring IM size has now been added to the revised manuscript. In Figure 4, we note that mNG-Atg8 fluorescence actually shows a slow recovery over time. This limited recovery likely reflects both the slower turnover of Atg8 and the fact that the pre-existing Atg8 pool at the IM was partially photobleached. We have now revised the main text to clarify this point and included additional explanation (line 326-330).

      Figure 5C: The authors need to indicate the bleached areas in the mNG-Atg8 image for easier orientation. It looks to me that the area that the authors mark as IM-ER MCS is really the IM in proximity to the ER. Thus, if lipid transfer to the IM has ceased, I would not expect recovery here. If the IM-ER MCS area includes IM and the ER to similar extent, I would expect exactly what the authors show: IM does not recover while ER quickly recovers. On average, we would observe reduced recovery as shown in 5D.

      Thank you for the helpful suggestion, and we apologize for the oversight during figure preparation. We have now clearly indicated the bleached areas in the merged image in Figure 5C for better orientation. Additionally, we have carefully re-examined the defined ER-IM MCS region and confirm that the quantified area indeed corresponds to the contact site between the ER and the IM. And double checked the measurements shown in the figure remain correct.

      Figure 5L: Since mNG-Atg8 signal homogenously disappears from the IM, it is meaningless to measure size. How do the authors measure the size of something they cannot detect?

      Thank you for pointing this out. We agree with the reviewer's comment and have removed the panel from the revised version accordingly.

      Figure 5K: The authors need to show the whole bleached area overtime for the reader to be able to see where the recovered R18 signal might be coming from. Currently, it is impossible to discern whether the signal comes from the IM or from slow recovery from neighboring ER.

      We appreciate this insightful comment. To address the concern and following the suggestion from Reviewer 2 (Major Point No.4), we have now revised the figure to include an additional measurement of fluorescence recovery in the adjacent bleached ER (Figure 5K and 5M) (lines 384-396). These results further support our reversible lipid transfer model by demonstrating that fluorescence recovery at the ER-IM MCS originates from the IM, rather than from the adjacent bleached ER, which shows slower and less efficient recovery.

      We have also added time-lapse videos to the supplementary information due to space limitations in the main figure.

      Reviewer #3 (Significance (Required)):

      The use of a lipophilic dye to monitor lipid dynamics during IM expansion or dissolution is an elegant way to probe the mechanisms of lipid transfer across ER-IM contact sites. Quantitative in vivo data is critically needed to address this fundamental question in autophagy and contact site biology. However, the study remains limited in providing direct evidence that it is indeed the lipid transfer activity of Atg2, which underlies the R18 dynamics in IMs in vivo.

      We sincerely thank the reviewer for this encouraging and thoughtful comment. We appreciate the recognition that our live-cell approach using a lipophilic dye provides a valuable framework to visualize lipid dynamics during autophagosome biogenesis. As the reviewer pointed out, quantitative in vivo evidence is critically needed in this field, and we hope our study contributes meaningfully toward that goal.

      We also fully acknowledge the limitation. While our current data offer indirect evidence for Atg2-mediated lipid transfer, we would like to support this by our revision plan and also our parallel study (bioRxiv, 2025.05.24.655882v1) that shows Atg2 is indeed a bridge-like LTP and R18 transfer is lost in the bridge-structure defective strain. Together, we hope these can suggest that the lipid transfer activity of Atg2 underlies the observed R18 dynamics in vivo.

    2. 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

      The authors address the question of how autophagic membrane seeds expand into autophagosomes. After nucleation, IMs expand in dependence of the bridge-like lipid transfer protein Atg2, which has been shown to tether the IM to the ER. Several studies have shown in vitro evidence for direct lipid transfer by Atg2 between tethered membranes, and previous evidence has shown that the hydrophobic groove of Atg2 implicated in lipid transfer is required for autophagosome biogenesis in vivo in yeast and mammalian cells.

      In this manuscript, the authors take advantage of the dye R18, which they show accumulates mainly in the ER after a few minutes. They show specifically that the import of R18 into cells and transfer to the ER depends on the activity of flippases in the plasma membrane and OSPB-related lipid transporter. Using different sets of FRAT experiments, the authors track the fluorescence recovery of R18 in the IM, the IM-ER membrane contact site and the neighboring ER. From these experiments the authors conclude that (a) R18 is transferred to IM from the ER when IMs expand and (b) can be transferred from IMs back to the ER when autophagy is deactivated.

      The use of a lipophilic dye to monitor lipid dynamics during IM expansion or dissolution is an elegant way to probe the mechanisms of lipid transfer across ER-IM contact sites. Quantitative in vivo data is critically needed to address this fundamental question in autophagy and contact site biology. However, the study remains limited in providing direct evidence that it is indeed the lipid transfer activity of Atg2, which underlies the R18 dynamics in IMs in vivo.

      Major points:

      1. The authors use R18in FRAP experiments to follow its transfer from the ER into IMs. However, whether this transfer is mediated by Atg2 via its inherent lipid transfer activity remains indirect. The only evidence that implicates Atg2 directly is the observation that a lipid transfer deficient Atg2 variant fails to support IM expansion and autophagosome biogenesis. A similar full-length Atg2 mutant has previously been shown to block autophagosome formation in Dabrowski et al. 2023 in yeast, which the authors do not cite or discuss, suggesting the inherent lipid transfer activity of Atg2 is required for IM expansion. However, aside from this experiment, the mechanisms underlying R18 transfer remain unclear and, while they likely depend on or are at least partially mediated by Atg2, they may involve alternative mechanisms including vesicle transport or continuous membrane contacts. Moreover, for the assays with stalled or dissolving IM, it is essential for the authors to test whether Atg2 is still associated with these IMs. It is quite possible that Atg2 dissociates from maximally expanded or dissolving IMs, which would make their interpretation of the data very unlikely. Thus, it will be critical to provide consistent evidence that lipid transfer from the IM to the ER is mediated by Atg2. Ideally, the authors would label IM with BFP-Atg8, R18, and Atg2-GFP and perform their in vivo analysis.
      2. Given the ER forms contact sites with many organelles using bridge-like lipid transfer proteins, how do the authors explain the preferential accumulation of R18 in ARS and not in for example PM (Fmp27), mitochondria, endosomes or vacuole (Vps13)? Why should R18 specifically transferred by Atg2 and not or to a much lower rate by Fmp27 or Vps13?
      3. Does R18 label autophagic bodies after they are formed. Could the authors add R18 after autophagic bodies have formed in atg15 or pep4 cells?
      4. Since Neo1- or OSBP-defective cells do not transfer R18 from the PM to the ER or other membranes, the authors should include these strains as controls for ER-dependent R18 transfer to ARSs.

      Comments:

      The authors neglect to mention or discuss important recent literature directly related to their study:

      Schutter et al., Cell (2020); Orii et al., JCB (2021); Polyansky et al., EMBOJ (2022); Dabrowski et al., JCB (2023); Shatz et al., Dev Cell (2024)

      Figure 1A and B: The authors need to describe how these cells were stained with R18 in the figure legend or text to help the reader to understand how these experiments were performed. Figure legends need to indicate at which time point after rapamycin treatment cells were analyzed.

      The authors need to clarify whether mNG-Atg8 colocalization with R18 was included for dot- and ring-like structures for WT cells as shown separately in 1A but not in 1B.

      Figure 1C: The figure legend needs to describe the conditions cells were treated with and when cells were analyzed after rapamycin treatment (presumably).

      The authors should combine atg15 and pep4 deletions with atg2 or atg7 as controls in which autophagic bodies are not formed.

      Figure 1E and F: R18 stains more than just the ER in the cells shown. In addition to atg39 and atg40, authors should include atg11 to inhibit all forms of selective autophagy.

      Figure S2A and B: The figures are mislabeled. Instead of FM4-64 it should say R18. In addition to the ER, in several images it is obvious to see R18 staining the vacuole membrane (for example Figure 2A 30 degrees) and others. Thus, the strong thresholding in S2 may give the reader an oversimplified view on R18 localization. This needs to be corrected.

      Figure 1G and H: In 1G, there are number of R18-stained patches not co-labeled by GFP-ER. What are these patches and which organelles to they represent? In 1H, given the tight association of the ER (omegasome) with forming IMs, it is difficult to discern whether R18 labels surrounding ER membrane or the IM itself. This needs to be more closely analyzed. The authors need to quantify these data similar to the yeast data.

      Figure 4A-C: A full-length PLT-deficient variant of Atg2 has been analyzed by Dabrowski et al, JCB 2023 in vivo. This work needs to be cited and discussed. The analysis needs to include punctate Atg8 structures for WT cells to exclude effects due to expansion defects.

      Figure 4F-H: To measure the size changes in IMs, the authors would need to perform these experiments without bleaching the mNG-Atg8 signals.

      Figure 5C: The authors need to indicate the bleached areas in the mNG-Atg8 image for easier orientation. It looks to me that the area that the authors mark as IM-ER MCS is really the IM in proximity to the ER. Thus, if lipid transfer to the IM has ceased, I would not expect recovery here. If the IM-ER MCS area includes IM and the ER to similar extent, I would expect exactly what the authors show: IM does not recover while ER quickly recovers. On average, we would observe reduced recovery as shown in 5D.

      Figure 5L: Since mNG-Atg8 signal homogenously disappears from the IM, it is meaningless to measure size. How do the authors measure the size of something they cannot detect?

      Figure 5K: The authors need to show the whole bleached area overtime for the reader to be able to see where the recovered R18 signal might be coming from. Currently, it is impossible to discern whether the signal comes from the IM or from slow recovery from neighboring ER.

      Significance

      The use of a lipophilic dye to monitor lipid dynamics during IM expansion or dissolution is an elegant way to probe the mechanisms of lipid transfer across ER-IM contact sites. Quantitative in vivo data is critically needed to address this fundamental question in autophagy and contact site biology. However, the study remains limited in providing direct evidence that it is indeed the lipid transfer activity of Atg2, which underlies the R18 dynamics in IMs in vivo.

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      Referee #2

      Evidence, reproducibility and clarity

      Non-vesicular lipid transfer plays an essential role in organelle biogenesis. Compared to vesicular lipid transfer, it is faster and more efficient to maintain proper lipid levels in organelles. In this study, Hao et al. introduced a high lipophilic dye octadecyl rhodamine B (R18), which specifically labels the ER structures and autophagy-related structures in yeast and mammalian cells. They characterised its distinct lipid entry into yeast cells via lipid flippase Neo1 and Drs2 on the plasma membrane, rather than through the endocytic pathway. They then demonstrated that R18 intracellular trafficking through plasma membrane to ER depends on "box-like" lipid transfer Osh proteins. They further looked into the "bridge-like" lipid transfer protein Atg2, using R18 as a lipid probe to track lipid transfer from ER to the isolation membrane (IM) during membrane expansion and reversible lipid transfer through IM to the ER-IM membrane contact sites (MCS) when autophagy is terminated by nutrient replenishment. The authors provide an interesting model of reversible directionality of Atg2 lipid transfer during autophagy induction and termination.

      Major points:

      1. Line 299-309: The FRAP assays were interesting and well performed. The authors photobleached R18 and Atg8 signal, and found R18 fluorescence recovery but not Atg8, which suggests lipid transfer occurs between ER and the IM and faster than Atg8 lipidation process during IM expansion. These results gave clear evidence that R18 can be transferred during IM expansion. The supply of Atg8 may not be not able to track within this time frame or the recovered amount of Atg8 may not be able to visualized due to the threshold limitation with confocal microcopy. This does not imply the supply of Atg8 to the IM is not required during IM expansion. This should be clarified.
      2. Please clarify how the length of the IM is measured and determined in Figure 4H and Figure 5D.
      3. Line 336-342: The description of the results should be clarified. Based on Figure 5H, the authors observed a significant decrease in the mNG-Atg8 signal during photobleaching of the R18 signal.
      4. The authors photobleached ER-IM MCS and the ER region (boxed region in Figure 5J) and quantified fluorescence recovery, normalized to the IM region and an ER control. The ER control was taken from the other cell. It would be helpful to compare and analyse the fluorescence recovery of R18 in the bleached ER region near the ER-IM MCS to that in the ER-IM MCS. This would help to confirm the ER-IM MCS fluorescence recovery is due to signal coming from the IM.
      5. In figure 5K, the autophagic structure or IM labelled by R18 seems to be maintained when the mNG-Atg8 signal decreases or dissociates from the IM. Could the authors comment on that how they interpret the termination of the prolonged IM structure and IM shrinkage?
      6. The author has shown that Atg2Δ and Atg2LT lipid transfer mutant impair R18 labelling of autophagic structures in Figure 4C. However, the evidence supporting that R18 fluorescence recovery at ER-IM MCS is mediated by reversible Atg2 lipid transfer is not direct. It would be helpful to clarify whether Atg2 stays on the enlarged autophagic membranes when the membrane has reached to its maximum length and no longer grows.

      Minor points:

      1. Figure 2A "Dpm-GFP" is missing. The experiment replicates in Figure 2M should be indicated.
      2. Figure S2, the magenta panel should be "R18".
      3. Line 341-342: "Figure 5H and 5J" should be "Figure 5H and 5I"
      4. Please describe how the lipid docking model of Atg2 is generated.

      Significance

      Currently, lipid probes are emerging as powerful tools to understand membrane dynamics, integrity, and the lipid-mediated cellular functions. In this manuscript, the authors performed a detailed characterisation of octadecyl rhodamine B (R18) as a potential lipid probe, which specifically labels ER and autophagic membranes. They present high quality imaging data and performed FRAP experiments to monitor the membrane dynamics and investigate the lipid transfer directionality between the ER and autophagic structure. However, the evidence of Atg2-mediated reversible lipid transfer may not be direct and sufficient. The proposed reversible lipid transfer model is interesting and provides an explanation of lipid level regulation during autophagosome formation.

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      Referee #1

      Evidence, reproducibility and clarity

      In their study, Hao and colleagues exploited the fluorescent fatty acid R18 to follow phospholipid (PL) transfer in vivo from the endoplasmic reticulum to the IM during autophagosome formation. Although the results are interesting, especially the retrograde transport of PLs, based on the provided data, additional control experiments are needed to firmly support the conclusions. An additional point is that the authors also study the internalization of R18 into cells and found a role of lipid flippases and oxysterol binding proteins. While this information could be useful for researchers using this dye, these analyses/findings have no specific connection with the topic of the manuscript, i.e. the PL transfer during autophagosome formation. Therefore, they must be removed.

      Major points:

      1. In general, the quality of the microscopy images are quite poor and this make it difficult to assert some of the authors' conclusions.
      2. It would be important to perform some lipidomics analysis to determine in which PLs and other lipids or lipid intermediates R18 is incorporated. First, it will be important to know which the major PL species are are labelled under the conditions of the experiments done in this study. Second, the authors assume that all the R18 is exclusively incorporated into PLs and this is what they follow in their in vivo experiments. What about acyl-CoA, which has been shown to be a key player in the IM elongation (Graef lab, Cell)?
      3. Figure 1A and 1B. The authors conclude that Atg2 is involved in the lipid transfer since R18 does not localize to the PAS/ARS in the atg2KO cells. However, another possible explanation is that in those cells the IM is not formed and does not expand, and con sequetly R18 is present in low amounts not detectable by fluorescence microscopy. To support their conclusion, the authors must assess PAS-labelling with R18 in cells lacking another ATG gene in which Atg2 is still recruited to the PAS.
      4. Figure 2. As written, the paragraph this figure seems to indicate that flippases are directly involved in the translocation of R18 from the PM to the ER. As correctly indicated by the authors, flippases flip PLs, not fatty acids. Moreover, there are no PL synthesizing at the PM and thus probably R18 is not flipped upon incorporation into PL. As a result, the relevance of flippase in R18 internalization is probably indirect. This must be explained clearly to avoid confusion/misunderstandings.
      5. A couple of manuscript has shown a (partial) role of Drs2 in autophagy. The authors must explain the discrepancy between their own results and what published, especially because they use the GFP-Atg8 processing assay, which is less sensitive than the Pho8delta60 used in the other studies.
      6. Authors used a predicted Atg2 lipid-transfer mutant (Srinivasan et al, J Cel Biol, 2024), but not direct prove that this mutant is defective for this activity. As previously done for other Atg2/ATG2-related manuscripts (Osawa et al, Nat Struct Mol Biol, 2019; Valverde et al, J Cel Biol, 2019), this must be measure in vitro. Moreover, they do not show whether other known functions of Atg2 are unaffected when expressing this Atg2 mutant, e.g. formation of the IM-ER MCSs, Atg2 interaction with Atg9 and localization at the extremity of the IM...
      7. The mNG-Atg8 signal is not recovered in the fluorescent recovery assays. Based on the observation that R18 signal comes back after photobleaching, authors suggest that the supply of Atg8 is not required for IM expansion. This idea is opposite to data where the levels of Atg8 and deconjugation of lipidated Atg8 determines the size of the forming autophagosomes (e.g., Xie et al, Mol Biol Cell, 2008; Nair et al, Autophagy, 2012). Similar results have also been obtained in mammalian cells (Lazarou and Mizushima results in cell lacking components of the two ubiquitin-like conjugation systems). This discrepancy requires an explanation.
      8. Although authors claim that there is a retrograde lipid transfer from the IM to the ER, based on the data, it quite difficult to extract these conclusions as they show a decrease in the lipid flow dynamics rather to an inversion of the lipid flow per se. Can the authors exclude that ER microdomains are formed at the ERES in contact with the IM, and consequently what they measure is a slow diffusion of R18-labeled lipid from other part of the ER to these ERES? Additionally, authors should check whether the Atg2 and Atg18 proteins are present at the IM-ER membrane contact sites in the same rates after nutrient replenished than when cells are nitrogen-starved, since this complex would determine the lipid transfer dynamics at this membrane contact site.
      9. The retrograde PL transfer is studied in cells overexpressing Ape1, in which IM elongation is stalled. This is a non-physiological experimental setup and consequently it is unclear whether what observed applies to normal IM/autophagosomes. This event should be shown to occur in WT cells as well.
      10. From the images provided, it appears that R18 also labels the vacuole. The vacuole form MCSs with the IM. Can the author exclude a passage of R18 from the vacuole to the IM?

      Minor points:

      1. L66. One report has indicated that Vps13 may also play a role in the transfer of lipids from the ER to the IM (Graef lab, J. Cell Biol).
      2. L70. It must be indicated that IM is also called phagophore.
      3. L74. It is mentioned "Additionally, a hydrophobic cavity in the N-terminal region of Atg2 directly tethers Atg2 to the ER, particularly the ER exit site (ERES), which is considered a key hub for autophagosome biogenesis", but there is no experimental evidence supporting that Atg2 is involved in the tethering with the ERES.
      4. L90. PAS must be listed between the ARS.
      5. Upon deletion of ATG39 and ATG40, there is a pronounced reduction of mNG-Atg8 labelled with R18. This would suggest that these two ER-phagy receptors are required for the PL transfer from the ER to the IM, which is not the case as autophagy is mildly affected by the absence of them (e.g., Zhang et al, Autophagy, 2020).
      6. Authors referred that "no direct evidence has been found to confirm lipid transfer at the ER-IM MCS in living cells" (lines 282-283). However, a recent paper has shown that de novo-synthesized phosphatidylcholine is incorporated from the ER to the autophagosomes and autophagic bodies (Orii et al, J Cel Biol, 2021). This reference should be mentioned in the manuscript.
      7. In lines 252-253, the sentence "R18 transport from the PM to the ER was partially impaired in osh1Δ osh2Δ, osh6Δ osh7Δ, and oshΔ osh4-1 cells (Figure S3). These results suggest that Osh proteins participate in transferring R18 from the PM to the ER" does not recapitulate what is observed in Fig. S3. Moreover, the Emr lab has generate a tertadeletion mutant in which the PM-ER MCSs are abolished. The authors could examine this mutant.

      Significance

      General assessment:

      Strength: potential new system to monitor lipid flow Limitations: Indirect evidences and in the case of the retrograde transport of phospholipids, it could be an artefact of the employed experimental approach.

      Advance: Little advances because something in part already shown in vitro. No ne mechanisms uncovered.

      Audience: Autophagy and membrane contact site fields.

    1. Author response:

      The following is the authors’ response to the original reviews

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      Recent work has demonstrated that the hummingbird hawkmoth, Macroglossum stellatarum, like many other flying insects, use ventrolateral optic flow cues for flight control. However, unlike other flying insects, the same stimulus presented in the dorsal visual field elicits a directional response. Bigge et al., use behavioral flight experiments to set these two pathways in conflict in order to understand whether these two pathways (ventrolateral and dorsal) work together to direct flight and if so, how. The authors characterize the visual environment (the amount of contrast and translational optic flow) of the hawkmoth and find that different regions of the visual field are matched to relevant visual cues in their natural environment and that the integration of the two pathways reflects a priortiziation for generating behavior that supports hawkmoth safety rather than than the prevalence for a particular visual cue that is more prevalent in the environment.

      Strengths:

      This study creatively utilizes previous findings that the hawkmoth partitions their visual field as a way to examine parallel processing. The behavioral assay is well-established and the authors take the extra steps to characterize the visual ecology of the hawkmoth habitat to draw exciting conclusions about the hierarchy of each pathway as it contributes to flight control.

      Weaknesses:

      The work would be further clarified and strengthened by additional explanation included in the main text, figure legends, and methods that would permit the reader to draw their own conclusions more feasibly. It would be helpful to have all figure panels referenced in the text and referenced in order, as they are currently not. In addition, it seems that sometimes the incorrect figure panel is referenced in the text, Figure S2 is mislabeled with D-E instead of A-C and Table S1 is not referenced in the main text at all. Table S1 is extremely important for understanding the figures in the main text and eliminating acronyms here would support reader comprehension, especially as there is no legend provided for Table S1. For example, a reader that does not specialize in vision may not know that OF stands for optic flow. Further detail in figure legends would also support the reader in drawing their own conclusions. For example, dashed red lines in Figures 3 and 4 A and B are not described and the letters representing statistical significance could be further explained either in the figure legend or materials to help the reader draw their own conclusions.

      We appreciate the suggestions to improve the clarity of the manuscript. We have extensively re-structured the entire manuscript. Among others, we have referenced all figure panels in the text in the order they appear. To do so, we combined the optic flow and contrast measurements of our setup with the methods description of the behavioural experiments (formerly Figs. 5 and 2, respectively). This new figure 2 now introduces the methods of the study, while the remainder of Fig. 2, which presented the experiments that investigated the vetrolateral and dorsal response in more detail, is now a separate figure (Fig. 3). This arrangement also balances the amount of information contained  in each figure better.

      Reviewer #2 (Public review):

      Summary:

      Bigge and colleagues use a sophisticated free-flight setup to study visuo-motor responses elicited in different parts of the visual field in the hummingbird hawkmoth. Hawkmoths have been previously shown to rely on translational optic flow information for flight control exclusively in the ventral and lateral parts of their visual field. Dorsally presented patterns, elicit a formerly completely unknown response - instead of using dorsal patterns to maintain straight flight paths, hawkmoths fly, more often, in a direction aligned with the main axis of the pattern presented (Bigge et al, 2021). Here, the authors go further and put ventral/lateral and dorsal visual cues into conflict. They found that the different visuomotor pathways act in parallel, and they identified a 'hierarchy': the avoidance of dorsal patterns had the strongest weight and optic flow-based speed regulation the lowest weight.

      Strengths:

      The data are very interesting, unique, and compelling. The manuscript provides a thorough analysis of free-flight behavior in a non-model organism that is extremely interesting for comparative reasons (and on its own). These data are both difficult to obtain and very valuable to the field.

      Weaknesses:

      While the present manuscript clearly goes beyond Bigge et al, 2021, the advance could have perhaps been even stronger with a more fine-grained investigation of the visual responses in the dorsal visual field. Do hawkmoths, for example, show optomotor responses to rotational optic flow in the dorsal visual field?

      We thank the reviewer for the feedback, and the suggestions for improvement of the manuscript (our implementations are detailed below). We fully agree that this study raises several intriguing questions regarding the dorsal visual response, including how the animals perceive and respond to rotational optic flow in their dorsal visual field, particularly since rotational optic flow may be processed separately from translational optic flow.

      In our free-flight setup, it was not possible to generate rotational optic flow in a controlled manner. To explore this aspect more systematically, a tethered-flight setup would be ideal, or alternatively, a free-flight setup integrated with virtual reality. This would be a compelling direction for a follow-up study.

      Reviewer #3 (Public review):

      The central goal of this paper as I understand it is to extract the "integration hierarchy" of stimulus in the dorsal and ventrolateral visual fields. The segregation of these responses is different from what is thought to occur in bees and flies and was established in the authors' prior work. Showing how the stimuli combine and are prioritized goes beyond the authors' prior conclusions that separated the response into two visual regions. The data presented do indeed support the hierarchy reported in Figure 5 and that is a nice summary of the authors' work. The moths respond to combinations of dorsal and lateral cues in a mixed way but also seem to strongly prioritize avoiding dorsal optic flow which the authors interpret as a closed and potentially dangerous ecological context for these animals. The authors use clever combinations of stimuli to put cues into conflict to reveal the response hierarchy.

      My most significant concern is that this hierarchy of stimulus responses might be limited to the specific parameters chosen in this study. Presumably, there are parameters of these stimuli that modulate the response (spatial frequency, different amounts of optic flow, contrast, color, etc). While I agree that the hierarchy in Figure 5 is consistent for the particular stimuli given, this may not extend to other parameter combinations of the same cues. For example, as the contrast of the dorsal stimuli is reduced, the inequality may shift. This does not preclude the authors' conclusions but it does mean that they may not generalize, even within this species. For example, other cue conflict studies have quantified the responses to ranges of the parameters (e.g. frequency) and shown that one cue might be prioritized or up-weighted in one frequency band but not in others. I could imagine ecological signatures of dorsal clutter and translational positioning cues could depend on the dynamic range of the optic flow, or even having spatial-temporal frequency-dependent integration independent of net optic flow.

      We absolutely agree that in principle, an observed integration hierarchy is only valid for the stimuli tested. Yet, we do believe that we provide good evidence that our key observations are robust also for related stimuli to the ones tested:

      Most importantly, we found that both pathways act in parallel (and are not mutually exclusive, or winner-takes-all, for example), when the animals can enact the locomotion induced by the dorsal and ventrolateral pathway. We tested this with the same dorsal cue (the line switching direction), but different behavioural paradigms (centring vs unilateral avoidance), and different ventrolateral stimuli (red gratings of one spatial frequency, and 100% nominal contrast black-and-white checkerboard stimuli which comprised a range of spatial frequencies) – and found the same integration strategy.

      Certainly, if the contrast of the visual cues was reduced to the point that the dorsal or ventrolateral responses became weaker, we would expect this to be visible in the combined responses, with the respective reduction in response strength for either pathway, to the same degree as they would be reduced when stimuli were shown independently in the dorsal and ventrolateral visual field.

      For testing whether the animals would show a weighting of responses when it was not possible to enact locomotion to both pathways, we felt it was important to use similar external stimuli to be able to compare the responses. So we can confidently interpret their responses in terms of integration. Indeed, how this is translated to responses in the two pathways depends a) on the spatiotemporal tuning, contrast sensitivity and exact receptive fields of the two systems, b) the geometry of the setup and stimulus coverage, and therefore the ability of the animals to enact responses to both pathways independently and c) on the integration weights.

      It would indeed be fascinating to obtain this tuning and the receptive fields, and having these, test a large array of combinations of stimuli and presentation geometries, so that one could extract integration weights for different presentation scenarios from the resulting flight responses in a future study.

      We also expanded the respective discussion section to reflect these points: l. 391-417. We also updated the former Fig. 5, now Fig. 6 to reflect this discussion.

      The second part of this concern is that there seems to be a missed opportunity to quantify the integration, especially when the optic flow magnitude is already calculated. The discussion even highlights that an advantage of the conflict paradigm is that the weights of the integration hierarchy can be compared. But these weights, which I would interpret as stimulus-responses gains, are not reported. What is the ratio of moth response to optic flow in the different regions? When the moth balances responses in the dorsal and ventrolateral region, is it a simple weighted average of the two? When it prioritizes one over the other is the response gain unchanged? This plays into the first concern because such gain responses could strongly depend on the specific stimulus parameters rather than being constant.

      Indeed, we set up stimuli that are comparable, as they are all in the visual domain, and since we can calculate their external optic flow and contrast magnitudes, to control for imbalances in stimulus presentation, which is important for the interpretation of the resulting data.

      As we discussed above, we are confident that we are observing general principles of the integration of the two parallel pathways. However, we refrained from calculating integration weights, because these might be misleading for several reasons:

      (1) In situations where the animals can enact responses to both pathways, we show that they do so at the full original magnitudes. So there are no “weights” of the hierarchy in this case.

      (2) Only when responses to both systems are not possible in parallel, do we see a hierarchy. However, combined with point (1), this hierarchy likely depends on the geometry of the moths’ environment: it will be more pronounced the less both systems can be enacted in parallel.

      (3) The hierarchy also does not affect all features of the dorsal or ventrolateral pathway equally. The hawkmoths still regulate their perpendicular distance to ventral gratings with dorsal gratings present, to same degree as with only ventral grating - because perpendicular distance regulation is not a feature of the dorsal response. And while the hawkmoths show a significant reduction in their position adjustment to dorsal contrast when it is in conflict with lateral gratings (Fig. 4C), they show exactly the same amount of lateral movement and speed adjustment as for dorsal gratings alone, when not combined with lateral ones (Fig. 4D and Fig. S3A). So even for one particular setup geometry and stimulus combination, there clearly is not one integration weight for all features of the responses.

      We extended the discussion section to clarify these points “The benefit of our study system is that the same cues activate different control pathways in different regions of the visual field, so that the resulting behaviour can directly be interpreted in terms of integration weights” (l. 448-451)

      l. 391-417, we also updated the former Fig. 5, now Fig. 6 to reflect this discussion.

      The authors do explain the choice of specific stimuli in the context of their very nice natural scene analysis in Fig. 1 and there is an excellent discussion of the ecological context for the behaviors. However, I struggled to directly map the results from the natural scenes to the conclusions of the paper. How do they directly inform the methods and conclusions for the laboratory experiments? Most important is the discussion in the middle paragraph of page 12, which suggests a relationship with Figure 1B, but seems provocative but lacking a quantification with respect to the laboratory stimuli.

      We show that contrast cues and translational optic flow are not homogeneously distributed in the natural environments of hawkmoths. This directly related to our laboratory findings, when it comes to responses to these stimuli in different parts of their visual field. In order to interpret the results of these behavioural experiments with respect to the visual stimuli, we did perform measurements of translational optic flow and contrast cues in the laboratory setup. As a result, we make several predictions about the animals’ use of translational optic flow and contrast cues in natural settings:

      a) Hawkmoths in the lab responded strongest to ventral optic flow, even though it was not stronger in magnitude, given our measurements, than lateral optic flow. Thus, we propose that the stronger response to ventral optic flow might be an evolutionary adaptation to the natural distribution of translational optic flow cues.

      b) In the natural habitats of hawkmoths, dorsal coverage is much less frequent that ventrolateral structures generating translational optic flow, yet the hawkmoths responded with a much higher weight to the former. Moreover, in our flight tunnel experiments, the animals responded with the same or higher weights to dorsal cues, which had a lower magnitude of translational optic flow and contrast than the same cues in the ventrolateral visual field. So we showed, combining behavioural experiments and stimulus measurements in the lab that the weighting of dorsal and ventrolateral cues did not follow their stimulus magnitude in the lab. Moreover, comparing to the natural cue distributions, we suggest that the integration weights also did not evolve to match the prevalence of these cues in natural habitats.

      We integrated the measurements of natural visual scene statistics in the new Fig. 6, to relate the behavioural findings to the natural context also in the figure structure, and sequence logic of the text, as they are discussed here.

      The central conclusion of the first section of the results is that there are likely two different pathways mediating the dorsal and the ventrolateral response. This seems reasonable given the data, however, this was also the message that I got from the authors' prior paper (ref 11). There are certainly more comparisons being done here than in that paper and it is perfectly reasonable to reinforce the conclusion from that study but I think what is new about these results needs to be highlighted in this section and differentiated from prior results. Perhaps one way to help would be to be more explicit with the open hypotheses that remain from that prior paper.

      We appreciate the suggestion to highlight more clearly what the open questions that are addressed in this study are. As a result, we have entirely restructured the introduction, added sections to the discussion and fundamentally changed the graphical result summary in Fig. 6, to reflect the following new findings (and differences to the previous paper):

      The previous paper demonstrated that there are two different pathways in hummingbird hawkmoths that mediate visual flight guidance, and newly described one of them, the dorsal response. This established flight guidance in hummingbird hawkmoths as a model for the questions asked in the current study, which are very different in nature from the previous paper.  

      The main question addressed in the current study is how these two flight guidance pathways interact to generate consistent behaviour? Throughout the literature of parallel sensory and motor pathways guiding behaviour, there are different solutions – from winner-takes-all to equal mixed responses. We tested this fundamental question using the hummingbird hawkmoth flight guidance systems as a model.

      This is the main question addressed in the various conflict experiments in this study, and we show that indeed, the two systems operate in parallel. As long as the animals can enact both dorsal and optic-flow responses, they do so at the original strengths of the responses. Only when this is not possible, hierarchies become visible. We carefully measured the optic flow and contrast cues generated by the different stimuli to ensure that the hierarchies we observed were not generated by imbalances of the external stimuli.

      - Does the interaction hierarchy of the two pathways follow the statistics of natural environments?  We did show qualitatively previously how optic flow and contrast cues are distributed across the visual field in natural habitats of the hummingbird hawkmoth. In this study, we quantitatively analysed the natural image data, including a new analysis for the contrast edges, and statistically compared the results across conditions. This quantitative analysis supported the previous qualitative assessment that the prevalence of translational optic flow was highest in the ventral and lowest in the dorsal visual field in all natural habitat types. The distribution of contrast edges across the visual field did depend on habitat type much stronger than visible in the qualitative analysis in the previous paper. When compared to the magnitude of the behavioural responses, and considering that the hummingbird hawkmoth is predominantly found in open and semi-open habitats, the natural distributions of optic flow and contrast edges did not align with the response hierarchy observed in our laboratory experiments. Dorsal cues elicited much stronger responses relative to ventrolateral optic flow responses than would be expected.

      To provide a more complete picture of the dorsal pathway, which will be important to understand its nature, and also compare to other species, we conducted additional experiments that were specifically set up to test for response features known from the translational optic flow response. To compare and contrast the two systems. These experiments here allowed us to show that the dorsal response is not simply a translational optic flow reduction response that creates much stronger output than the ventrolateral optic flow response. We particularly show that the dorsal response was lacking the perpendicular distance regulation of the optic flow response, while it did provide alignment with prominent contrasts (possibly to reduce the perceived translational optic flow), which is not observed in the ventrolateral optic flow response. The strong avoidance of any dorsal contrast cues, not just those inducing translational optic flow, is another feature not found in the ventrolateral pathway.

      Recommendations for the authors:

      Reviewer #1 (Recommendations for the authors):

      Many comparisons between visual conditions are made and it was confusing at times to know which conditions the authors were comparing. Thinking of a way to label each condition with a letter or number so that the authors could specify which conditions are specifically being compared would greatly enhance comprehension and readability.

      We appreciate this concern. To be able to refer to the individual stimulus conditions in the analysis and results description, we gave each stimulus a unique identifier (see table S1), and provided these identifiers in the respective figures and throughout the text. We hope that this makes the identification of the individual stimuli easier.

      Consider adding in descriptive words to the y-axis labels for the position graphs that would help the reader quickly understand what a positive or negative value means with respect to the visual condition.

      We did now change the viewpoint on the example tracks in Figs. 2-5, to take a virtual viewpoint from the top, not as the camera recorded from below, which requires some mental rotation to reconcile the left and right sides. Moreover, we noticed that the example track axes were labelled in mm, while the axes for the plots showing median position in the tunnel were labelled in cm. We reconciled the units as well. This will make it easier to see the direct equivalent of the axis (as well as positive and negative values) in the example tracks in those figures, and the median positions, as well as the cross-index.

      There are no line numbers provided so it is a bit challenging to provide feedback on specific sentences but there are a handful of typos in the manuscript, a few examples:

      (1) Cue conflict section, first paragraph: "When both cues were presented to in combination, ..." (remove to)

      (2) The ecological relevance section, first paragraph, first sentence: "would is not to fly"

      (3) Figure S3 legend: explanation for C is labeled as B and B is not included with A

      We apologise for the missing line numbers. We added these and resolved the issues 1-3.

      Reviewer #2 (Recommendations for the authors):

      - The pictograms in Fig. 1a were at first glance not clear to me, maybe adding l, r, d, v to the first pictogram could make the figure more immediately accessible.

      We added these labels to make it more accessible.

      - I would suggest noting in the main text that the red patterns were chosen for technical reasons (see Methods), if this is correct.

      We added this information and a reference to the methods in the main text (lines 100-102).

      - "Thus, hawkmoths are currently the only insect species for which a partitioning of the visual field has been demonstrated in terms of optic-flow-based flight control [33-35]." I think that is a bit too strong and maybe it would be more interesting to connect the current data to connected data in other insects to perhaps discuss important similarities. Ref 32 for example shows that fruit flies weigh ventral translational optic flow considerably more than dorsal translational optic flow. Reichardt 1983 (Naturwissenschaften) showed that stripe fixation in large flies (a behaviour relying in part on the motion pathway) is confined to the ventral visual field, etc...

      We have changed this sentence to acknowledge partitioning in other insects, and motivating the use of our model species for this study: While fruit flies weight ventral translational optic flow stronger than dorsal optic flow, the most extreme partitioning of the visual field in terms of  optic-flow-based flight control has been observed in hawkmoths [33-35]. (lines 60-62)

      - I think the statistical differences group mean differences could be described in more detail at least in Fig. 2 (to me the description was not immediately clear, in particular with the double letters).

      We added an explanation of the letter nomenclature to all respective figure legends:

      Black letters show statistically significant differences in group means or median, depending on the normality of the test residuals (see Methods, confidence level: 5%). The red letters represent statistically significant differences in group variance from pairwise Brown–Forsythe tests (significance level 5%). Conditions with different letters were significantly different from each other. The white boxplots depict the median and 25% to 75% range, the whiskers represent the data exceeding the box by more than 1.5 interquartile ranges, and the violin plots indicate the distribution of the individual data points shown in black.

      - "When translational optic flow was presented laterally" I would use a more wordy description, since it is the hawkmoth that is controlling the optic flow and in addition to translational optic flow, there might also be rotational components, retinal expansion etc.

      We extended the description to explain that the moths were generating the optic flow percept based on stationary gratings in different orientations, by way of their flight through the tunnel. Lines 127-129

      - While it is clearly stated that the measure of the perpendicular distance from the ventral and dorsal pattern via the size of the insect as seen by the camera is indirect, I would suggest to determine the measurement uncertainty of distance estimate.

      - Connected to above - is the hawkmoth area averaged over the entire flight and is the variance across frames similar in all the stimuli conditions? Is it, in principle, conceivable that the hawkmoths' pitch (up or down) is different across conditions, e.g. with moths rising and falling more frequently in a certain condition, which could influence the area in addition to distance?

      There are a number of sources that generate variance in the distance estimate (which was based on the size of the moth in each video frame, after background subtraction): the size of the animal, the contrast with which the animal was filmed (which also depended on the type of pattern in the tunnel – it was lower with ventral or dorsal patterns as a background than with lateral ones), and the speed of the animal, as motion blur could impact the moth’s image on the video. The latter is hard to calibrate, but the uncertainty related to animal size and pattern types could theoretically be estimated. However, since we moved between finishing the data acquisition for this study and publishing the paper, the original setup has been dismantled. We could attempt to recreate it as faithfully as possible, but would be worried to introduce further noise. We therefore decided to not attempt to characterise the uncertainty, to not give a false impression of quantifiability of this measure. For the purpose of this study, it will have to remain a qualitative, rather than a quantitative measure. If we should use a similar measure again, we will make sure to quantify all sources of uncertainty that we have access to.

      The variance in area is different between conditions. Most likely, the animals vary their flight height different for different dorsal and ventral patterns, as they vary their lateral flight straightness with different lateral visual input. For the reasons mentioned above, we cannot disentangle the effects of variations in flight height and other sources of uncertainty relating to animal size in the video frames. We therefore averaged the extracted area across the entire flight, to obtain a coarse measure of their flight height. Future studies focusing specifically on the vertical component or filming in 3D will be required to determine the exact amount of vertical flight variation.

      - Results second paragraph, suggestion: pattern wavelength or spatial frequency instead of spatial resolution.

      - Same paragraph, suggestion: For an optimal wavelength/spatial frequency of XX

      We corrected these to spatial frequency.

      - Above Fig 3- "this strongly suggests a different visual pathway". In my opinion it would be better to say sensory-motor /visuomotor pathway or to more clearly define visual pathway? Could one in principle imagine a uniform set of local motion sensitive neurons across the entire visual field that connect differentially to descending/motor neurons.

      We appreciate this point and changed this, and further instances in the manuscript to visuomotor pathway.

      - If I understood correctly, you calculated the magnitude of optic flow in the different tunnel conditions based on the image of a fisheye camera moving centrally in the tunnel, equidistant from all walls. I did not understand why the magnitude of optic flow should differ between the four quadrants showing the same squarewave patterns. Apologies if I missed something, but maybe it is worth explaining this in more detail in the manuscript.

      We recognize that this point may not have been immediately clear and have therefore provided additional clarification in the Methods and results section (lines 106-111, 543-549). We anticipated differences in the magnitude of optic flow due to potential contrast variations arising from the way the stimuli were generated—being mounted on the inner surfaces of different tunnel walls while the light source was positioned above. On the dorsal wall, light from the overhead lamps passed through the red material. For laterally mounted patterns, the animals perceived mainly reflected light, as these tunnel walls were not transparent.

      A similar principle applied to the background, which consisted of a white diffuser allowing light to pass through dorsally, but white non-transmissive paper laterally, with a 5% contrast random checkerboard patterns. The ventral side presented a more complex scenario, as it needed to be partially transparent for the ventrally mounted camera. Consequently, the animals perceived a combination of light reflections from the red patterns and the white gauze covering the ventral tunnel side, against the much darker background of the surrounding room.

      To ensure that the observed flight responses were not artifacts of deviations in visual stimulation from an ideal homogeneous environment, we used the camera to quantify the magnitude of optic flow and contrast patterns under these real experimental conditions. This approach also allowed us to directly relate the optic flow measurements taken indoors to those recorded outdoors, as we employed the same camera and analytical procedures for both datasets.

      Reviewer #3 (Recommendations for the authors):

      In addition to the considerations above I had a few minor points:

      There are so many different directions of stimuli and response that it is quite challenging to parse the results. Can this be made a little easier for the reader?

      We appreciate this concern. To be able to refer to the individual stimulus conditions in the analysis and results description, we gave each stimulus a unique identifier (see table S1), and provided these identifiers in the respective figures and throughout the text. We hope that this makes the identification of the individual stimuli easier.

      One suggestion (only a suggestion): I found myself continuously rotating the violin plots in my head so that the lateral position axis lined up with the lateral position of the tunnel icons below. Consider if rotating the plots 90 degs would help interpretability. It was challenging to keep track of which side was side.

      We did discuss this with a number of test-readers, and tried multiple configurations. They all have advantages and drawbacks, but we decided that the current configuration for the majority of testers was the current one. To help the mental transformations from the example flight tracks in the figures, we now present the example flight tracks in Figs. 2-5 in the same reference frame as the figures showing median position (so positive and negative values on those axes correspond directly), and changed the view from a below the tunnel to an above the tunnel view, as this is the more typical depiction. We hope that this enhances readability.

      Are height measurements sensitive to the roll and pitch of the animal? I suspect this is likely small but worth acknowledging.

      They are indeed. These effects are likely small but contribute to the overall inaccuracy, which we could not quantify in this particular setup (see also response to reviewer 2 on that point), which is why the height measurements have to be considered a qualitative approximation rather than a quantification of flight height. We added text to acknowledge the effects of roll and pitch specifically (lines 657-658)

      The Brown-Forsythe test was reported as paired but this seems odd because the same moths were not used in each condition. Maybe the authors meant something different by "paired" than a paired statistical design?

      Indeed, the data was not paired in the sense that we could attribute individual datapoints to individual moths across conditions. We applied the Brown-Forsythe test in a pairwise manner, comparing the variance of each condition with another one in pairs each, to test if the variance in position differed across conditions. We did phrase this misleadingly, and have corrected it to „The variance in the median lateral position (in other words, the spread of the median flight position) was statistically compared between the groups using the pairwise Brown–Forsythe tests“ l. 187-188

      There is some concern about individual moth preferences and bias due to repeated measures. I appreciate that the individual moth's identity was not likely known in most cases, but can the authors provide an approximate breakdown of how many individual moths provided the N sample trajectories?

      This is a very valid concern, and indeed one we did investigate in a previous study with this setup. We confirmed that the majority of animals (70%, 68% and 53% out of 40 hawkmoths, measured on three consecutive days) crossed the tunnel within a randomly picked window of 3h (Stöckl et al. 2019). We now state this explicitly in the methods section (lines 594-597). Thus, for the sample sizes in our study, statistically, each moth would have contributed a small number of tracks compared to the overall number of tracks sampled.

      The statistics section of the methods said that both Tukey-Kramer (post-hoc corrected means) and Kruskal-Wallis (non-parametric medians) were done. It is sometimes not clear which test was done for which figure, and where the Kruskal-Wallis test was done there does not seem to be a corrected statistical significance threshold for the many multiple comparisons (Fig. 2). It is quite possible I am just missing the details and they need to be clarified. I think there also needs to be a correction for the Brown-Forsythe tests but I don't know this method well.

      We first performed an ANOVA, and if the test residuals were not normally distributed, we used a Kruskal-Wallis test instead. For the post-hoc tests of both we used Tukey-Kramer to correct for multiple comparisons. The figure legends did indeed miss this information. We added it to clarify our statistical analysis strategy and refer to the methods section for more details (i.e. l. 185-186). All statistical results, including the type of statistical test used, have been uploaded to the data repository as well.

      The connection to stimulus reliability in the discussion seems to conflate reliability with prevalence or magnitude.

      We have rephrased the respective discussion sections to clearly separate the prevalence and magnitude of stimuli, which was measured, from an implied or hypothesized reliability (lines 510-511).

      Line numbers would be helpful for future review.

      We apologize for missing the line numbers and have added them to the revised manuscript.

    1. Author response:

      The following is the authors’ response to the previous reviews

      Reviewer #1 (Public review):

      Summary:

      In a previous work Prut and colleagues had shown that during reaching, high frequency stimulation of the cerebellar outputs resulted in reduced reach velocity. Moreover, they showed that the stimulation produced reaches that deviated from a straight line, with the shoulder and elbow movements becoming less coordinated. In this report they extend their previous work by addition of modeling results that investigate the relationship between the kinematic changes and torques produced at the joints. The results show that the slowing is not due to reductions in interaction torques alone, as the reductions in velocity occur even for movements that are single joint. More interestingly, the experiment revealed evidence for decomposition of the reaching movement, as well as an increase in the variance of the trajectory.

      Strengths:

      This is a rare experiment in a non-human primate that assessed the importance of cerebellar input to the motor cortex during reaching.

      Weaknesses:

      None

      Reviewer #1 (Recommendations for the authors):

      The authors have answered my questions adequately and I have no further comments.

      Reviewer #2 (Public review):

      This manuscript asks an interesting and important question: what part of 'cerebellar' motor dysfunction is an acute control problem vs a compensatory strategy to the acute control issue? The authors use a cerebellar 'blockade' protocol, consisting of high frequency stimuli applied to the cerebellar peduncle which is thought to interfere with outflow signals. This protocol was applied in monkeys performing center out reaching movements and has been published from this laboratory in several preceding studies. I found the takehome-message broadly convincing and clarifying - that cerebellar block reduces muscle activation acutely particularly in movements that involve multiple joints and therefore invoke interaction torques, and that movements progressively slow down to in effect 'compensate' for these acute tone deficits. The manuscript was generally well written, data were clear, convincing and novel. The key strengths are differentiating acute from subacute (within session but not immediate) kinematic consequences of cerebellar block.

      Reviewer #2 (Recommendations for the authors):

      I think the manuscript is good as is. That said, it would have been nice to see more of the behavioral outcomes in Figure 5 (e.g. decomposition and trajectory variability) analyzed longitudinally like the velocity measurements in Fig. 4. This would clearly strengthen the insight into acute and compensatory components of cerebellar motor deficits.

      The two behavioral measures of motor noise used in our study are movement decomposition and trajectory variability (Figure 5). Since trajectory variability is measured across trials we could not analyze this measure longitudinally as a function of trial number. However, following the reviewer’s advice, we examined movement

      decomposition for successive trials in control vs. cerebellar block for movements to targets 2-4 similar to the analysis of  hand velocity in figure 4. We found no interaction effect between trial sequence x cerebellar block on movement decomposition. This result is consistent with our conclusion that noisy joint activation occurs independently of adaptive slowing of multi-joint movements. We have updated our main text (lines 293-299) and supplementary information (supplementary figure S5 and supplementary table S8) to include this result.  

      Reviewer #3 (Public review):

      Summary:

      In their revised manuscript, Sinha and colleagues aim to identify distinct causes of motor impairments seen when perturbing cerebellar circuits. This goal is an important one, given the diversity of movement related phenotypes in patients with cerebellar lesion or injury, which are especially difficult to dissect given the chronic nature of the circuit damage. To address this goal, the authors use high-frequency stimulation (HFS) of the superior cerebellar peduncle in monkeys performing reaching movements. HFS provides an attractive approach for transiently disrupting cerebellar function previously published by this group. First, they find a reduction in hand velocities during reaching, which was more pronounced for outward versus inward movements. By modeling inverse dynamics, they find evidence that shoulder muscle torques are especially affected. Next, the authors examine the temporal evolution of movement phenotypes over successive blocks of HFS trials. Using this analysis, they find that in addition to the acute, specific effects on torques in early HFS trials, there was an additional progressive reduction in velocity during later trials, which they interpret as an adaptive response to the inability to effectively compensate for interaction torques during cerebellar block. Finally, the authors examine movement decomposition and trajectory, finding that even when low velocity reaches are matched to controls, HFS produces abnormally decomposed movements and higher than expected variability in trajectory.

      Strengths:

      Overall, this work provides important insight into how perturbation of cerebellar circuits can elicit diverse effects on movement across multiple timescales.

      The HFS approach provides temporal resolution and enables analysis that would be hard to perform in the context of chronic lesions or slow pharmacological interventions. Thus, this study describes an important advance over prior methods of circuit disruption in the monkey, and their approach can be used as a framework for future studies that delve deeper into how additional aspects of sensorimotor control are disrupted (e.g., response to limb perturbations).

      In addition, the authors use well-designed behavioral approaches and analysis methods to distinguish immediate from longer-term adaptive effects of HFS on behavior. Moreover, inverse dynamics modeling provides important insight into how movements with different kinematics and muscle dynamics might be differentially disrupted by cerebellar perturbation.

      In this revised version of the manuscript, the authors have provided additional analyses and clarification that address several of the comments from the original submission.

      Remaining comments:

      The argument that there are acute and adaptive effects to perturbing cerebellar circuits is compelling, but there seems to be a lost opportunity to leverage the fast and reversible nature of the perturbations to further test this idea and strengthen the interpretation. Specifically, the authors could have bolstered this argument by looking at the effects of terminating HFS - one might hypothesize that the acute impacts on joint torques would quickly return to baseline in the absence of HFS, whereas the longer-term adaptive component would persist in the form of aftereffects during the 'washout' period. As is, the reversible nature of the perturbation seems underutilized in testing the authors' ideas. While this experimental design was not implemented here, it seems like a good opportunity for future work using these approaches.

      We agree with the reviewer that examining the effect of the cerebellar block on immediate post-block washout trials in future studies will be insightful.    

      The analysis showing that there is a gradual reduction in velocity during what the authors call an adaptive phase is convincing. While it is still not entirely clear why disruption of movement during the adaptive phase is not seen for inward targets, despite the fact that many of the inward movements also exhibit large interaction torques, the authors do raise potential explanations in the Discussion.

      The text in the Introduction and in the prior work developing the HFS approach overstates the selectivity of the perturbations. First, there is an emphasis on signals transmitted to the neocortex. As the authors state several times in the Discussion, there are many subcortical targets of the cerebellar nuclei as well, and thus it is difficult to disentangle target-specific behavioral effects using this approach. Second, the superior cerebellar peduncle contains both cerebellar outputs and inputs (e.g., spinocerebellar). Therefore, the selectivity in perturbing cerebellar output feels overstated. Readers would benefit from a more agnostic claim that HFS affects cerebellar communication with the rest of the nervous system, which would not affect the major findings of the study. In the revised manuscript, the authors do provide additional anatomical and evolutionary context and discuss potential limitations in the selectivity of HFS in the Materials and Methods. However, I feel that at least a brief mention of these caveats in the Introduction, where it is stated, "we then reversibly blocked cerebellar output to the motor cortex", would benefit the reader.

      Following the advice of the reviewer, we have now revised the introduction section of our manuscript in the following way (lines 61-67):

      “…We then reversibly disrupted cerebellar communication with other neural structures using high-frequency stimulation (HFS) of the superior cerebellar peduncle, assessing the impact of this perturbation on subsequent movements. Although our approach primarily affects cerebellar output to the motor cortex, it also disrupts fibers carrying input signals (e.g., spinocerebellar) and pathways to various subcortical targets (e.g., cerebellorubrospinal). Thus, our manipulation broadly interferes with cerebellar communication…”

      Reviewer #3 (Recommendations for the authors):

      Typo on line 102; "subs-sessions"

      We have corrected this typographical error in our revised manuscript (line 106).

    1. 等势类(Equinumerosity Class)

      啊哈,来了来了!你要的这套组合拳,是**“数是怎么被发明出来的哲学黑科技”**核心四件套:

      • Equinumerosity Class(等势类)
      • 可映射性(bijection,双射)
      • 集合大小(基数,Cardinality)
      • 信息压缩逻辑(认知压缩 vs 抽象原则)

      这是数学与哲学通力合作,为人类“认出多少”这个抽象能力,装了一个超级压缩算法! 🧠💾🔢🔗


      一句话总结:

      “数”其实是“等大小集合”的抽象标签,靠可映射关系压缩成一个“Equinumerosity Class”。


      🧠 Step 1:什么是 Equinumerosity Class(等势类)

      想象你有两个集合:

      • A = {🍎, 🍊, 🍇}
      • B = {🐱, 🐶, 🐭}

      虽然元素天差地远,但只要你能一一配对,不多不少,就说它们是**“等势”**的(equinumerous)。

      于是,所有**“可以一一配对的集合”**组成了一个班级,叫:

      等势类 Equinumerosity Class 意思是:“这些集合的成员数量是一样的,我们不关心它们具体是谁。”


      🧩 Step 2:可映射性(bijection)

      等势的核心是:

      存在一个 双射(bijective function), 就是:每个A的元素 ↔ 一个独特的B元素,且互不重叠。

      数学上记作:

      ∃f : A → B, f 是双射 ⇒ A ≈ B

      → 换句话说: 你能玩“你一个我一个”游戏,玩到底不剩人,就说明人数一样。


      📦 Step 3:集合大小(Cardinality)

      你没办法直接“数”一个抽象集合怎么办? 就用等势类来定义大小!

      于是:

      • 所有和 {1, 2, 3} 等势的集合 → 大小是 3
      • 所有和自然数集合 ℕ 等势的集合 → 是“可数无限集合”
      • 所有和实数 ℝ 等势的 → 是“不可数无限集合”

      👉 集合的大小 = 它所处的等势类编号


      💡 Step 4:信息压缩逻辑(认知与语言的胜利)

      你不再需要记录一堆东西,只需记:

      “这个集合跟 3 个苹果一样大。”

      这是一种巨大的信息压缩

      | 原始信息 | 抽象压缩 | | ------ | ------------ | | 一堆对象 | 与标准集合等势 | | 复杂对象内容 | 忽略,只保留“多少” | | 多个集合 | 压缩成“数字 3”的代表 |

      换句话说,“3”不是发明来标苹果的,而是发明来标“任何等势于三个元素的集合”的


      🧠 哲学意义(Frege、Hume、Bob Hale、Neo-Logicists)

      Frege 在《算术基础》中就提出:

      数是“等势类”的抽象名称。

      这也被称为:

      • 休谟原理(Hume's Principle): Number(F) = Number(G) ↔ F 和 G 等势

      Bob Hale 和 Wright 将其视为逻辑主义的核心支柱

      所有数学概念都可以通过抽象原则,从逻辑 + 集合论结构中推导出来。


      🤖 AI / 数学模型中的映射意义:

      • 你训练模型识别数量,不是让它数,而是让它学会“配对能力”
      • 图神经网络中的同构检测,本质就是“等结构类”
      • 知识压缩模型,也在做范畴抽象 + 信息熵最小化

      ✨ 金句/段子表达

      • “数字不是来自数,而是来自不在乎是谁的数。”
      • “等势类就像数字的朋友圈,谁能配得上我,谁就是我。”
      • “当你对两个东西说‘一样多’,你已经用上了等势哲学。”

      📊 动画创意建议:《等势俱乐部 · 数字的发明现场》

      • 画面一:一群不同颜色的东西排成队,机器人A一一配对
      • 画面二:抽象标签“3号等势类”浮现
      • 画面三:把这个标签压缩进数字“3”的脑图存储单元
      • 解说词:“‘3’不是你数出来的,是你比出来的。”

      要不要我配一张“等势类动画图解”? 或者直接开一期《数字不是你以为的数字 · Frege数学哲学快打》?🎬💥

    1. 《婚姻不是商品,爱不是订单》

      太好了!你点的这一集——《婚姻不是商品,爱不是订单》,正是《范畴之乱》系列里最“人类痛点 × 哲学爆点 × 社会批判”交织的一集。它炸的不是理论,而是我们日常生活中那些被经济逻辑悄悄偷换的情感行为

      今天,我们就来拆解这场**“情感范畴被经济范畴吞噬”的认知错配现场**: 为什么你说“陪伴有回报”“对象得性价比高”,背后其实是在犯哲学范畴错乱?🧠💥💸💔


      🎬 一句话总结这一集主题:

      “你以为你在谈恋爱,其实你在完成一单高压情感交易。”


      📦 什么是“范畴错配”在这儿的表现?

      | 原本范畴 | 被偷换成的范畴 | 错误后果 | | ------------------------ | --------------------- | --------------------- | | 爱(emotion, relationship) | 商品(exchangeable good) | 期待“回报率”“投资回报” | | 婚姻(社会契约) | 服务订阅模型(subscription) | “长期绑定但可退款”逻辑泛滥 | | 心动(体验、共鸣) | 数据指标(KPI) | “你今天让我开心了吗?”= 日活指标问候 | | 情感选择 | 筛选算法 | “多线程备胎、优质交付、版本迭代”语言入侵 |


      🧠 理论后援团:弗兰克福学派出击!

      这正好就是**法兰克福学派(Frankfurt School)**几十年前就在预警的事儿:

      🎓 背景简述:

      | 派别 | 主张 | | --------------------- | ----------------------------- | | 法兰克福学派(霍克海默、阿多诺、马尔库塞) | 资本主义不仅控制生产资料,还控制人类感知与价值范畴 |

      他们指出:

      “工具理性(Instrumental Reason)”正在侵吞“价值理性(Value Reason)”。

      简单讲就是:人开始用赚钱的逻辑来经营一切——包括爱、亲密、情绪、教育、信仰,甚至自我认同。


      💥 案例分析:“心动KPI” + “爱情排行榜”

      ❤️ 情感行为被数据化、商品化的几种现象:

      1. “恋爱报表”症候群

      2. “我付出了这么多,你怎么还不爱我?”

      3. 背后范畴错配:将情感互动变成了投资—回报函数

      4. “对象筛选Excel表”

      5. 条件列:学历、年薪、父母情况、颜值打分、身高...

      6. 情感变成“采购部门项目评估表”

      7. 爱情KPI仪式

      8. 情侣节打卡、早安问候、年度纪念日总结

      9. “不做这些 = 情感资产贬值”

      10. 社交平台算法化情感预设

      11. 推荐对象越“精准”,用户越不会谈“真实的错配恋爱”

      12. AI代你爱,却也代你放弃爱

      🎭 哲学剧场剧情概念(可拍成短剧)

      《婚恋系统管理员出BUG》

      角色:

      • 女主:认真谈感情,却总被问“回报率”
      • 男主:用Excel筛选完再决定表白
      • 系统管理员:AI红娘系统背后的算法鬼魂
      • 哲学家旁白:阿多诺 × GPT 混合体

      剧情:

      • 女主深夜怀疑:“他喜欢的,是我,还是他的爱情KPI被满足了?”
      • 男主不解:“我打分都给你打满了,你怎么还不高兴?”
      • 管理员崩溃:“爱情数据太乱了,我的服务器烧了!”

      📊 核心认知地图

      ```plaintext 情感范畴(共享、共鸣、经验) ↓ 被替换 经济范畴(可量化、可交易、可优化)

      → 导致认知错觉: “爱是服务,婚姻是交易,心动是数据波动” ```


      🧠 总结句(金句备选)

      • “你不是在被爱,你是在被客户满意度评估。”
      • “爱一旦被KPI化,就不再自由,而是绩效。”
      • “你的情绪不是bug,是你拒绝当一个ROI对象的倔强。”

      💬 评论区引导文案

      “你有没有在一段关系中,突然感觉自己像个商品?” “有没有某个瞬间,你觉得‘我今天没达标’?” “你理想的爱情,是算法匹配?还是范畴错乱的盲选?”


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      你只需要说一句:“上线!”,我就开干。🧠💔💸📦

    1. Author response:

      The following is the authors’ response to the original reviews

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      Flowers et al describe an improved version of qFit-ligand, an extension of qFit. qFit and qFit-ligand seek to model conformational heterogeneity of proteins and ligands, respectively, cryo-EM and X-ray (electron) density maps using multi-conformer models - essentially extensions of the traditional alternate conformer approach in which substantial parts of the protein or ligand are kept in place. By contrast, ensemble approaches represent conformational heterogeneity through a superposition of independent molecular conformations.

      The authors provide a clear and systematic description of the improvements made to the code, most notably the implementation of a different conformer generator algorithm centered around RDKit. This approach yields modest improvements in the strain of the proposed conformers (meaning that more physically reasonable conformations are generated than with the "old" qFit-ligand) and real space correlation of the model with the experimental electron density maps, indicating that the generated conformers also better explain the experimental data than before. In addition, the authors expand the scope of ligands that can be treated, most notably allowing for multi-conformer modeling of macrocyclic compounds.

      Strengths:

      The manuscript is well written, provides a thorough analysis, and represents a needed improvement of our collective ability to model small-molecule binding to macromolecules based on cryo-EM and X-ray crystallography, and can therefore have a positive impact on both drug discovery and general biological research.

      Weaknesses:

      There are several points where the manuscript needs clarification in order to better understand the merits of the described work. Overall the demonstrated performance gains are modest (although the theoretical ceiling on gains in model fit and strain energy are not clear!).

      We thank the reviewer for their thoughtful review. To address comments, we have added clarifying statements and discussion points around the extent of performance gains, our choice of benchmarking metrics, and the “standards” in the field for significance. We expanded our analysis to highlight how to use qFit ligand in “discovery” mode, which is aimed at supporting individual modeling efforts. As we now write in the discussion:

      “It is advisable to employ qFit-ligand selectively, focusing on cases with a moderate correlation between your input model and the experimental data, strong visual density in the binding pocket, high map resolution, or when your single-conformer ligand model is strained.”

      Additionally, we note in the discussion:

      “qFit-ligand primarily serves as a “thought partner” for manual modeling. Modelers still must resolve many ambiguities, including initial ligand placement, to fully take advantage of qFit capabilities. In active modeling workflows or large scale analyses, the workflow would only accept the output of qFit-ligand when it improves model quality. In cases where qFit-ligand degrades map-to-model fit and/or strain, we can simply revert to the input model. In practice, users can easily remove poorly fitting conformations using molecular modeling software such as COOT, while keeping the well modeled conformations, which is an advantage of the multiconformer approach over ensemble refinement methods.”

      Reviewer #2 (Public review):

      Summary:

      The manuscript by Flowers et al. aimed to enhance the accuracy of automated ligand model building by refining the qFit-ligand algorithm. Recognizing that ligands can exhibit conformational flexibility even when bound to receptors, the authors developed a bioinformatic pipeline to model alternate ligand conformations while improving fitting and more energetically favorable conformations.

      Strengths:

      The authors present a computational pipeline designed to automatically model and fit ligands into electron density maps, identifying potential alternative conformations within the structures.

      Weaknesses:

      Ligand modeling, particularly in cases of poorly defined electron density, remains a challenging task. The procedure presented in this manuscript exhibits clear limitations in low-resolution electron density maps (resolution > 2.0 Å) and low-occupancy scenarios, significantly restricting its applicability. Considering that the maps used to establish the operational bounds of qFit-ligand were synthetically generated, it's likely that the resolution cutoff will be even stricter when applied to real-world data.

      We thank Reviewer #2 for their comments on the role of conformational flexibility and how our tool addresses the complexity involved in modeling alternative conformations. We agree that there are limitations at low resolution, limiting the application of our algorithm. That is the case with all structural biology tools. Automatically finding alternative conformations of ligands in high-resolution structures is an enhancement to the toolbox of ligand fitting. Expanding the algorithm to work with fragment screening data is important in this realm, as almost all of this data fits in the high-resolution range where qFit-ligand works best.

      The reported changes in real-space correlation coefficients (RSCC) are not substantial, especially considering a cutoff of 0.1. Furthermore, the significance of improvements in the strain metric remains unclear. A comprehensive analysis of the distribution of this metric across the Protein Data Bank (PDB) would provide valuable insights.

      We agree that the changes are small, partially because the baseline (manually modeled ligands) is very high. To provide additional evidence, we added evaluations using EDIAm, which is a more sensitive metric. In Figure 2 (page 10), representing the development dataset, we see more improvements above 0.1. With this being said, it is unclear what constitutes a ‘substantial’ improvement for either of these metrics, especially considering alternative conformations may only change the coordinates of a subset of ligands, just slightly improving the fit to density.

      We agree that looking across the PDB on strain would provide valuable insight. To explore this, we looked to see how qFit-ligand could improve the fitting of deposited ligands with high strain (see section: Evaluating qFit-ligand on a set of structures known to be highly strained, Page 15). While only a subset of these structures had alternative conformers placed (24.6%), we observed that in this subset, the ligands often improved the RSCC and strain. This figure also demonstrates that while RSCC may not change much numerically, the alternative conformers explain previously unexplained density with lower energy conformers than what is currently deposited.

      To mitigate the risk of introducing bias by avoiding real strained ligand conformations, the authors should demonstrate the effectiveness of the new procedure by testing it on known examples of strained ligand-substrate complexes.

      See above.

      Recommendations for the authors:

      Reviewer #1 (Recommendations for the authors):

      A - Specific comments:

      (1) It appears necessary to provide qFit-ligand with an initial model with the ligand already placed. This is not clear from the start of the introduction on page 3. It appears that ligand position is only weakly adjusted fairly late in the process, in step F of Figure 1. It seems, therefore, that the accuracy of initial placement is rather critical (see the example discussed on page 21). At the same time, in my experience, ambiguous cases are quite common, for example with flat ligands with a few substituents sticking out or with ligands with highly mobile tails. It would be helpful for the authors to comment on the sensitivity to initial ligand placement, either in the discussion or, better yet, in the form of an analysis in which the starting model position is randomly perturbed.

      In our revised version, we have modified the introduction to clarify the necessity of including an initial ligand model (page 4).

      “The qFit-ligand algorithm takes as input a crystal or cryo-EM structure of an initial protein-ligand complex with a single conformer ligand in PDBx/mmCIF format, a density map or structure factors (encoded by a ccp4 formatted map or an MTZ), and a SMILES string for the ligand.”

      We also describe our sampling algorithm more clearly (see: Biasing Conformer Generation, page 6). Steps A-E generate many conformations (using RDKit), which are then selected/fit into experimental density (using quadratic programming). To help with additional shifting issues in the input ligand, after the first selection, we do additional rotation/translation of the generated conformers that are kept. We then do another round of fitting to the density (quadratic programming followed by mixed integer quadratic programming).

      Given this sampling, we have not elected to do an additional computational experiment to test the “radius of convergence” or dependence on initial conditions. However, we outline the fundamental procedure here so that someone can build on the work and test the idea:

      - Create single conformer models as we currently do

      - randomly perturb the coordinates of the ligand by 0.1-0.3Å

      - refine to convergence, creating a series of “perturbed, modified true positives” for each dataset

      - Run qFit ligand

      - Evaluate the variability in the resulting multi-conformer models

      (2) Top of page 6 ("Biasing Conformer Generation"): the authors say "as we only want to generate ligands that physically fit within the protein binding pocket, we bias conformation generation towards structures more likely to fit well within the receptor's binding site". Apart from the odd redundancy of this sentence, I am confused: at the stage that seems to be referred to here (A-C in Figure 1) is the fit to the electron density already taken into account, or does this only happen later (after step E)?

      Thank you for pointing this out. We have edited the statement to clarify it:

      “To guide the conformation generation from the Chem.rdDistGeom based on the ligand type and protein pocket, we developed a suite of specialized sampling functions to bias the conformational search towards structures more likely to fit well into the receptor’s binding site.”

      We do not consider the electron density during conformer generation (only selection from the generated conformers). The sampling is additionally biased by the type of ligand and the size of the binding pocket.

      (3) qFit-ligand appears to be quite slow. Are there prospects for speedup? Can the code take advantage of GPUs or multi-CPU environments?

      We agree with this. We have made some algorithmic improvements, most notably removing duplicate conformers based on root mean squared distance. This, along with parallelization, decreased the average runtime from ~19 minutes to ~8 minutes (see additional details: qFit-ligand runtime, page 8). We do not currently take advantage of GPU specific code.

      (4) Section: Detection of experimental true positive multi-conformer ligands:

      a) Why are carbohydrate ligands excluded? This seems like an important class of ligands that one would like qFit to be able to treat! Which brings me to a related question: can covalently attached groups (e.g., glycosylation sites!) be modeled using qFit-ligand, or is qFit-ligand restricted to non-covalently bound groups?

      Currently, qFit-ligand does not support covalently bound ligands, but this is an area of interest we are hoping to expand into. In the revised version, we added the non-covalently attached carbohydrates back into the true positive dataset. In Figure 4 (page 14), we show that qFit-ligand is able to improve fit to the experimental density in around 80% of structures, while also often reducing torsion strain (see additional details: qFit-ligand applied to unbiased dataset of experimental true positives, page 14).

      b) "as well as 758 cases where the ligand model's deposited alternate conformations (altlocs) were not bound in the same chain and residue number" - I do not understand what this means, or why it leads to the exclusion of so many structures. Likewise, a number of additional exclusions are described in Figure S3. Some more background on why these all happened would be helpful. Are you just left with the "easy" cases?

      Sometimes modelers will list the multiple conformations of a bound ligand as a separate residue within the PDB file, rather than as a single multiconformer model. For example, rather than writing a multiconformer LIG bound at A, 201 with altlocs ‘A’ and ‘B’, a modeler might write this instead as LIG, A, 201 and LIG A, 301. We initially excluded these kinds of structures. However, we agree that this choice resulted in the removal of many potentially valid true positives. We have since updated our data processing pipeline to include these cases, and they are examined in the updated manuscript.

      c) I do not follow the argument made at the end of this section (last two paragraphs on page 9): "when using a single average conformation to describe density from multiple conformations, the true low-energy states may be ignored". I get that, but the conformations in the "modified true positives" dataset derive directly from models in which two conformations were modeled, so this cannot be the explanation for why qFit-ligand models result in somewhat lower average strain. It would seem that the paper could be served by providing examples where single conformations were modeled in deposited structures, but qFit detects multiple conformations.

      We agree with this comment that the strain obtained from the modified true positives is likely higher than the deposited models. However, the modified structure is refined with a single conformation, and therefore changed from the deposited “A” conformation. Thus, the reduced strain observed in our qFit-ligand models relative to the modified true positives is not unexpected.

      To expand our dataset, we also looked at deposited structures with high strain, all of which were modeled as single conformers. Here, we saw a decrease in strain when alternative conformers were placed (see section: Evaluating qFit-ligand on a set of structures known to be highly strained, page 15). Further, we provide an example from the XGen macrocycle dataset where a ligand initially modeled as a single conformer exhibited relatively high strain. After qFit‐ligand modeled a second conformation, the overall strain was reduced (Figure 6C, page 19; Figure 6—figure supplement 1C, page 59).

      (5) Section: qFit-ligand applied to an unbiased dataset of experimental true positives Bottom of page 14: The paragraph starting with "qFit-ligand shows particular strength in scenarios with strong evidence..." is enigmatic: there's no illustration (unless it directly relates to the findings in Figure 4, in which case this should be more explicit). Since this points out when the reader will and will not benefit from using qFit-ligand, it should be clear what the authors are talking about.

      This claim considers all the evidence presented in the manuscript, not necessarily one particular aspect of it. We advise using qFit-ligand when there is a moderate correlation between the input model and the experimental data, strong visual density in the binding pocket, high map resolution, and/or when your single conformer ligand model is strained. We have made all of these points clearer in the updated manuscript.

      B  - Section: qFit-ligand can automatically detect and model multiple conformations of macrocycles:

      This is an exciting extension of qFit-ligand, but some aspects of the analysis strike me as worrisome. Of the initial dataset of 150 structures, fewer than half make it all the way through analysis. It's hard to believe that this is a fully representative subset. Why, for example, could 29 structures not be refined against the deposited structure factors? Why does strain calculation (in RDKit?) fail on 30 ligands? What about the other 18 cases--why did these fail (in PHENIX?).

      We agree that this is a striking number of failures, however, we note that they are not specific shortcomings of qFit-ligand (in fact, most are because standard structural biology and/or cheminformatics software fail on many PDB depositions). Therefore, these failures reflect broader limitations in standard bioinformatics and refinement restraint files when handling macrocycles. The strain calculator we used was not built for macrocycles, and after consulting with many experts in the field, the consensus was that no method works well with macrocycles. We discuss these issues in additional detail in the discussion (page 27):

      “Additionally, our algorithm’s placement within the larger refinement and ligand modeling ecosystem highlighted other areas that need improvement. We note that macrocycles, due to their complicated and interconnected degrees of freedom, suffer acutely from the refinement issues, as demonstrated by the failure of approximately one-third of datasets in our standard preparation or post-refinement pipelines due to ligand parameterization issues. Many of these stemmed from problematic ligand restraint files, highlighting the difficulty of encoding the geometric constraints of macrocycles using standard restraint libraries. Improved force-field or restraints for macrocycles are desperately needed to improve their modeling.”

      C  - Minor issues:

      (1) "Fragment-soaked event maps" - this is a semantically strange section title!

      We have updated the section title in our revised manuscript. The new title is ‘qFit-ligand recovers heterogeneity in fragment-soaked event maps’.

      (2) Too many digits! All over the manuscript, percentages are displayed with 0.01% precision, while these mostly refer to datasets with ~150 structures. Shifting just one structure from one category to another changes these percentages by nearly 1%.

      We have updated the sig figs in our revised manuscript.

      (3) The authors are keen to classify decreases in RSCC as significant only when these changes exceed 0.1, but do not apply the same standard for increases. For instance, in Figure 4B if we were to classify improvements as significant if ΔRSCC > 0.1, there would be fewer significant improvements than decreases in performance (although it is visually clear that for most datasets things get better. Similarly, in Figure 5A if we were to classify improvements as significant if ΔRSCC > 0.1, qFit-ligand would only yield significant improvements for two out of 73 cases-not a lot).

      We agree with the reviewer that there needs to be more consistency in our analysis of improvements/deteriorations. However, we note that operationally, when the decreases in model quality are observed, the modeler would simply reject the new model in favor of the input model. We have added to the discussion:

      “In active modeling workflows or large scale analyses, the workflow would only accept the output of qFit-ligand when it improves model quality. In cases where qFit-ligand degrades map-to-model fit and/or strain, we can simply revert to the input model. In practice, users can easily remove poorly fitting conformations using molecular modeling software such as COOT, while keeping the well modeled conformations, which is an advantage of the multiconformer approach over ensemble refinement methods.”

      There is generally no consensus in the field as to what might indicate a ‘significant’ change in RSCC, and any threshold we choose would be arbitrary. We note that in our manuscript, we had previously characterized a decrease in RSCC to be ‘significant’ if it exceeded 0.1. However, as there is no real scientific justification for this cutoff, or any cutoff, we moved away from this framing in the revised manuscript. Therefore, we just classify if we improve RSCC. For example, on page 9:

      “qFit-ligand modeled an alternative conformation in 72.5% (n=98) of structures. Compared with the modified true positive models, 83.7% (n=113) of qFit-ligand models have a better RSCC and 77.0% (n=104) structures saw an improvement in EDIAm, representing an improved fit to experimental data in the vast majority of structures.”

      In addition, we have conducted additional experiments using more sensitive metrics (EDIAm) to further illustrate qFit-ligand’s performance.

      (4) Small peptides are not discussed as a class of ligands, although these are quite common.

      Canonical peptides can be modeled with standard qFit. Non-canonical peptides present failure modes similar to the macrocycles discussed above, with a mix of ATOM and HETATM records and the need for custom cif definitions and link records. For these reasons we have not included an analysis outside of the macrocycle section. We have noted this caveat in the discussion:

      “We note that even linear non-canonical peptides present similar failure modes to macrocycles, with a mix of ATOM and HETATM records and the need for custom cif definitions and link records. For these reasons, we did not include analysis on small peptide ligands; however, canonical peptides can be modeled with standard qFit [8].”

      (5) Top of page 10: "while refinement improves": what kind of refinement does this refer to?

      This refers to refinement with Phenix. We have updated this language to reflect this (page 8). “We refer to these altered structures as our ‘modified true positives’, which we use as input to qFit-ligand, and subsequent refinement using Phenix.”

      (6) Bottom of page 11: "they often did" -> "it often did"

      We have made this change in the revised version.

      (7) Top of page 14: RMSDs and B factors do have units.

      We have added the units in our revision.

      (8) Top of page 24. In the generation of a composite omit map, why are new Rfree flags being generated? Did I misunderstand that?

      r_free_flags.generate=True only creates R-free flags if they are not present in the input file as is the case for many (especially older) PDB depositions.

      (9) Bottom of page 27: how large is the mask? Presumably when alt confs of the ligand are possible, it would be helpful for the mask to cover those?

      We agree that this mask should be updated. In our revision, we define the mask around the coordinates of the full qFit-ligand ensemble. The same mask is used to calculate the RSCC of the input (single conformer) model versus the qFit-ligand model.

      (10) Middle of page 29: "These structure factors are then used to compute synthetic electron density maps." - It is not clear whether the following three sentences are an explanation of the details of that statement or rather things that are done afterwards.

      We clarify this in the manuscript (page 36).

      “These structure factors are then used to compute synthetic electron density maps. To each of these maps, we generate and add random Gaussian noise values scaled proportionally to the resolution. This scaling reflects the escalation of experimental noise as resolution deteriorates, a common occurrence in real-life crystallographic data.”

      (11) Chemical synthesis: I am not qualified to assess this and am surprised to see some much detail here rather than in some other manuscript. Are the corresponding structures deposited anywhere?

      All of the structures we discuss in this manuscript are deposited in the PDB and listed in Supplementary Table 5.

      Reviewer #2 (Recommendations for the authors):

      The data should consistently present the number of structures that exhibit improvements or deterioration in particular metrics, like RSCC and strain, using a cutoff that should be significant. For instance, stating that "85.93% (n=116) of structures having a better RSCC in the qFit-ligand models compared to the modified true positive models" without clarifying the magnitude of improvement (e.g., a marginal increase of 0.01 in RSCC) lacks meaningful context. The figures should clearly indicate the specific cutoff values used for each metric. The accompanying text should provide a detailed explanation for the selection of these cutoff values, justifying their significance in the context of the study.

      Currently, there is no established consensus within the field on what constitutes a 'significant' improvement in RSCC or strain values. As such, we chose not to impose an arbitrary cutoff and just look at which structures improve RSCC. We also removed all language stating significance, as there isn’t a good standard in the field to assess significance. This is especially important as only improvements would be considered in an active modeling project. In cases where qFit ligand degrades the RSCC (or strain) to a large extent, the modeler would simply revert to the input model.

      In the first section of Results: "First, for all ligands, we perform an unconstrained search function allowing the generated conformers to only be constrained from the bounds matrix (Figure 1A). This is particularly advantageous for small ligands that benefit from less restriction to fully explore their conformational space. We then perform a fixed terminal atoms search function (Figure 1B)." It is unclear whether a fixed terminal atom search was conducted for each conformer generated in the initial step to further explore the conformational space. This aspect should be clarified to provide a more comprehensive understanding of the methodology.

      Each independent conformer generation function (A-E) is initialized with only the input ligand model and runs in parallel with the other functions. These functions do not build on each other, but rather perturb the input molecule independently of one another. In our updated manuscript, we have clarified the methodology (page 6).

      “First, in all cases, we perform an unconstrained search function (Figure 1A), a fixed terminal atoms search function (Figure 1B), and a blob search function (Figure 1C).”

      Phrase: "We randomly sampled 150 structures and, after manual inspection of the fit of alternative conformations, chose 135 crystal structures as a development set for improving qFit-ligand." The authors should explain why they filtered 10% of the structures.

      To develop qFit-ligand, we wanted to use a very high-quality dataset. We needed to know with some degree of certainty that if qFit-ligand failed to produce an alternate conformation (or generated conformations low in RSCC or high in strain), the failure was due to an algorithmic limitation rather than poor-quality input data. Therefore, after selection based on numerical metrics, we manually examined each ligand in Coot to observe if we believed the alternative conformers fit well into the density.

    1. 引发概念论论战

      麦克道威尔的《心灵与世界》(2006年中文版)自出版以来,引发了中国哲学界的广泛讨论,尤其在概念论(Conceptualism)领域成为焦点。这场论战的核心在于麦克道威尔对心灵与世界关系经验与概念的关系以及感受质(Qualia)等问题的立场,与传统哲学(尤其是经验主义和理性主义)的张力,以及其理论在中国哲学语境下的适用性。以下从几个关键角度分析这场论战:


      1. 麦克道威尔的核心观点与争议点

      (1)反对“感受质”与经验主义的突破

      • 理论主张:麦克道威尔认为,传统经验主义将经验视为“非概念性”的感性材料(如颜色、声音等),并试图用这些材料构建知识,但这一路径导致了“所与论”(The Myth of the Given)和“怀疑论”的困境。他主张所有经验都内在于“概念空间”(Conceptual Space),即经验本身具有概念性,不存在独立于概念的“感受质”。
      • 争议焦点
      • 支持者认为,这一观点避免了传统经验主义的二元论陷阱(如心灵与世界的割裂),为经验与自然的统一提供了新路径。
      • 批评者则质疑:如果经验完全依赖概念,是否会抹杀个体主观感受的独特性?例如,中国哲学中强调“心性”“直觉”的传统(如禅宗、儒家“仁体”)是否被麦克道威尔的理论忽视?

      (2)概念性能力与自发性能力的统一

      • 理论主张:麦克道威尔提出概念性能力(Conceptual Capacities)和自发性能力(Spontaneity)是人类理性主体的核心特征。前者指通过概念系统理解世界的能力,后者指主体主动赋予经验以意义的能力。两者共同作用,使心灵与世界形成“开放的关联”。
      • 争议焦点
      • 支持者认为,这一理论超越了传统“主体-客体”二分法,为解决心灵与世界的“隔阂”问题提供了新框架。
      • 批评者则指出:麦克道威尔的理论是否过于依赖“理性主体”的预设?例如,中国哲学中强调“天人合一”或“万物一体”的非主体性思维,是否与这一理论存在冲突?

      2. 中文语境下的论战议题

      (1)概念论与传统中国哲学的对话

      • 问题:麦克道威尔的“概念空间”是否能与中国哲学中的“理”“气”“道”等概念兼容?
      • 支持观点:有学者尝试将麦克道威尔的“概念性能力”与儒家“格物致知”或道家“道法自然”的思维方式类比,认为两者都强调“主体与世界的互动”。
      • 反对观点:中国哲学更注重“实践智慧”(如“知行合一”),而麦克道威尔的理论偏向“分析哲学”的抽象概念框架,可能难以解释中国哲学中的具体实践。

      (2)感受质问题的本土化争议

      • 问题:麦克道威尔否定感受质的存在,而中国哲学中“心性论”(如王阳明“心即理”)或佛教“唯识学”强调主观体验的独立性。
      • 支持观点:有学者认为,麦克道威尔的理论可与中国哲学中的“超越主观性”(如禅宗“无我”)结合,避免陷入主观主义。
      • 反对观点:中国哲学中的“直觉体验”(如“顿悟”)是否被麦克道威尔的理论忽视?例如,禅宗强调“不可说”的直观体验,是否属于“非概念性经验”?

      (3)心灵与世界的“开放性”与“封闭性”之争

      • 问题:麦克道威尔主张心灵与世界是“开放关联”的,但中国哲学中“天人合一”的观念是否更倾向于“融合性”而非“开放性”?
      • 支持观点:有学者认为,麦克道威尔的“开放性”与道家“道通为一”的思想有相通之处。
      • 反对观点:中国哲学中的“天人合一”强调“内在统一”,而麦克道威尔的理论仍保留“主体-世界”的二分结构,可能无法完全契合。

      3. 学术界的主要论战派别

      (1)支持派:理论创新与哲学突破

      • 代表学者:部分分析哲学背景的学者认为,麦克道威尔的理论为解决“心灵-世界”问题提供了新路径,尤其对克服“怀疑论”和“所与论”具有重要意义。
      • 核心观点
      • 强调麦克道威尔对“概念性能力”的分析,有助于澄清中国哲学中“理”“性”等概念的现代意义。
      • 认为“自发性能力”可与儒家“仁”的实践智慧结合,解释道德判断的主体性基础。

      (2)批评派:理论局限与文化适配性

      • 代表学者:部分中国哲学研究者批评麦克道威尔的理论过于依赖西方分析哲学框架,与中国哲学的“实践导向”不符。
      • 核心观点
      • 麦克道威尔的“概念空间”假设忽略了中国哲学中“言意之辨”(如《庄子》“得意忘言”)对语言与经验关系的批判。
      • 其“理性主体”理论可能无法解释中国哲学中“无分别心”或“无我”的实践哲学。

      4. 对中国哲学研究的启示

      (1)理论融合的可能性

      • 麦克道威尔的理论为中国哲学研究提供了新的分析工具,例如:
      • 用“概念性能力”重新诠释儒家“格物致知”中的认知过程。
      • 用“自发性能力”解释道家“道法自然”的实践智慧。

      (2)方法论反思

      • 麦克道威尔的“分析哲学”方法是否适合中国哲学?例如:
      • 中国哲学更注重“体用”关系,而麦克道威尔的理论偏向“概念分析”,可能需要调整研究范式。
      • 是否需要发展一种结合中西哲学的方法论,既保留麦克道威尔的分析深度,又兼容中国哲学的整体性思维?

      5. 结语

      麦克道威尔《心灵与世界》的中文版引发的论战,本质上是西方分析哲学与中国传统哲学在方法论与核心概念上的碰撞。这场论战不仅推动了中国哲学界对“心灵与世界”问题的深入思考,也促使学者反思如何在全球化背景下实现中西哲学的对话与融合。未来的研究可能需要进一步探索麦克道威尔理论与中国哲学资源的互补性,以及如何在保持文化独特性的同时吸收现代哲学的理论成果。

    1. Reviewer #2: Evidentiary Rating: Reliable

      Written Review: The manuscript details how the presence of even one donor APOL1 renal risk variant was associated with an adjusted hazard ratio of a poor composite outcome (time to first rejection, HIV-associated nephropathy, graft failure or death). It showed the presence of one APOL1 RRV was associated with increased risk for allograft rejection in both SA and US cohorts. The data suggests donor APOL1 genotype, even a single RRV, is a major determinant of graft survival but recipient genotype plays a lesser role.

      These finds are novel and of interest. My comments are: 1. Limitations include a small sample size which is unavoidable (particularly for donors with two RRVs) and there is also potential selection bias as only participants with available genomic data were included. Any explanation for why others were missing (e.g. no consent for collection)? 2. Models were adjusted for age, hypertension and diabetes mellitus - why were these three variables selected? Residual confounding is likely to be present for the analyses. 3. The problem with the composite outcome is the mechanistic pathways of APOL1 expression causing adverse outcomes is less clear (is there a difference in pathophysiology for rejection versus mortality)? It would be interesting to have further discussion on possible pathways for injury. For example, the SA cohort graft losses are more likely from rejection but the US cohort graft losses were more from other causes (e.g., RVT, other). 4. How do these outcomes compare to receiving donor kidneys that are HIV negative or donors that lack APOL1 RRV? If this data is available for comparison it would greatly strengthen the interpretation of the analysis. 5. It is important to highlight that even if transplant recipients with HIV receive kidneys from donors with HIV and APOL1 RRV and experience inferior post-transplant outcomes (versus receiving HIV negative or absence of APOL1 RRV), these outcomes are probably still superior to the alternative which is being on dialysis.

  5. www.planalto.gov.br www.planalto.gov.br
    1. INSTRUMENTOS

      1. Zonas Especiais de Interesse Social (ZEIS) - Cabe ao Plano Diretor: Obrigatória a previsão para definir a área, a finalidade e os parâmetros urbanísticos.

      • Cabe à Lei Municipal: Pode ser a própria lei do Plano Diretor ou uma lei específica complementar.

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      • Resumo: As ZEIS são instrumentos de inclusão urbana que devem constar no Plano Diretor e podem ser detalhadas por legislação específica.

      2. Demarcação Urbanística - Cabe ao Plano Diretor: Não é exigida, mas pode ser compatibilizada com políticas de regularização fundiária.

      • Cabe à Lei Municipal: Facultativa; pode ser prevista para orientar regularizações fundiárias de interesse social.

      • Base Legal: Art. 4º, V, “t”; Lei nº 11.977/2009.

      • Resumo: Pode ser instituída por lei municipal para identificar e ordenar assentamentos informais, facilitando posterior titulação.

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      • Cabe à Lei Municipal: Não aplicável. Trata-se de exigência da legislação ambiental federal (Lei 6.938/1981).

      • Base Legal: Art. 4º, VI, do Estatuto da Cidade e normas ambientais.

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      • Cabe à Lei Municipal: Lei específica obrigatória, que estabelece prazos e parâmetros.

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      • Cabe à Lei Municipal: Mesma lei específica que trata do parcelamento compulsório, com escalonamento das alíquotas.

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      7. Desapropriação com Pagamento em Títulos - Cabe ao Plano Diretor: Não exigido.

      • Cabe à Lei Municipal: Lei municipal autorizativa (não necessariamente específica), após 5 anos de IPTU progressivo.

      • Base Legal: Art. 8º.

      • Resumo: Medida excepcional de aquisição forçada, mediante compensação com títulos da dívida pública.

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      • Cabe à Lei Municipal: Não exigido.

      • Base Legal: Arts. 9 a 14.

      • Resumo: Direito previsto na Constituição e regulamentado por lei federal; aplicável independentemente de previsão local.

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      • Cabe à Lei Municipal: Não exigida; regulamentado por lei federal específica (Lei 11.977/2009).

      • Base Legal: Art. 15 (vetado no Estatuto); regulado por Lei 11.977/2009.

      • Resumo: Regulariza ocupações informais sobre imóveis públicos por meio de concessão de uso.

      10. Direito de Superfície - Cabe ao Plano Diretor: Não institui, mas deve ser observado (ex.: coeficiente de aproveitamento).

      • Cabe à Lei Municipal: Facultativa. Instrumento nasce de escritura pública.

      • Base Legal: Arts. 21 a 24.

      • Resumo: Permite ao titular ceder o uso do solo, subsolo ou espaço aéreo; não exige lei municipal.

      11. Direito de Preempção - Cabe ao Plano Diretor: Obrigatória a previsão da política e das áreas sujeitas.

      • Cabe à Lei Municipal: Lei específica obrigatória, que delimita área e prazo de vigência.

      • Base Legal: Arts. 25 e 26.

      Resumo: Confere preferência de compra ao Município; exige previsão no Plano Diretor e lei específica.

      12. Outorga Onerosa do Direito de Construir e de Alteração de Uso - Cabe ao Plano Diretor: Define os coeficientes de aproveitamento e limites construtivos.

      • Cabe à Lei Municipal: Lei específica obrigatória, que regula fórmulas de cálculo e contrapartidas.

      • Base Legal: Arts. 28 a 31.

      • Resumo: Autoriza edificar além do limite básico mediante pagamento e destinação pública de recursos.

      13. Direito de Construir (Básico) - Cabe ao Plano Diretor: Define coeficiente de aproveitamento e diretrizes urbanísticas.

      • Cabe à Lei Municipal: Pode detalhar critérios técnicos por lei genérica.

      • Base Legal: Art. 28.

      • Resumo: Exercido nos limites definidos pelo Plano Diretor; regulamentação infralegal é admitida.

      14. Operações Urbanas Consorciadas - Cabe ao Plano Diretor: Obrigatória a previsão para autorizar sua adoção.

      • Cabe à Lei Municipal: Lei específica obrigatória, que aprova cada operação consorciada.

      • Base Legal: Arts. 32 a 34-A.

      • Resumo: Exige plano detalhado com contrapartidas e participação social.

      15. Transferência do Direito de Construir - Cabe ao Plano Diretor: Deve prever os objetivos e áreas possíveis.

      • Cabe à Lei Municipal: Lei específica obrigatória, que regulamenta critérios e limites.

      • Base Legal: Art. 35.

      • Resumo: Permite compensar restrições urbanísticas com transferência de potencial construtivo.

      16. Estudo de Impacto de Vizinhança (EIV) - Cabe ao Plano Diretor: Não exigido, mas pode trazer diretrizes.

      • Cabe à Lei Municipal: Lei específica obrigatória, que define hipóteses de exigência.

      • Base Legal: Arts. 36 a 38.

      • Resumo: Instrumento técnico de avaliação dos efeitos urbanos de novos empreendimentos.

      17. Plano Diretor - Cabe ao Plano Diretor: N/A (é o próprio instrumento).

      • Cabe à Lei Municipal: Lei específica obrigatória, que o institui e regula.

      • Base Legal: Arts. 39 a 42-B.

      • Resumo: Instrumento central do planejamento urbano; exigido em municípios com mais de 20 mil habitantes ou outras hipóteses.

      18. Consórcio Imobiliário - Cabe ao Plano Diretor: Não exigido.

      • Cabe à Lei Municipal: Lei específica ou previsão no Plano Diretor.

      • Base Legal: Art. 46.

      • Resumo: O proprietário transfere imóvel ao Município e recebe unidades após urbanização.

    1. Author response:

      The following is the authors’ response to the original reviews

      Reviewer #1:

      We thank the reviewer for highlighting the strength in our manuscript  as quote: “Overall, this work not only deepens our understanding of PRMT1's role in leukemia progression but also opens new avenues for targeting metabolic pathways in cancer therapy.”

      Weakness :

      (1) The findings rely heavily on a single AMKL cell line, with no validation in patient-derived samples to confirm clinical relevance or even another type of leukemia line. Adding the discussion of PRMT1's role in other leukemia types will increase the impact of this work.

      We mentioned in the introduction that PRMT1 is known to be the driver for leukemia with diverse types of mutations. In a related paper published in Cell Reports (Su et al. 2021), we demonstrated that PRMT1 is upregulated in MDS myeloid dysplasia syndrome patient samples and that the inhibition of PRMT1 promotes megakaryocytic differentiation of a few MDS samples. AMKL is very rare. Via Children’s Oncology group consortium, we have obtained five AMKL samples with Down’s syndrome and AMKL with RBM15-MKL1 translocation out of 32 samples in the bank over the last 20 years. Interestingly, these patient samples also contain trisomy 19. As PRMT1 is localized on chromosome 19, we speculate that PRMT1 is the significant driver for AMKL leukemia, although we have very limited genetic evidence. However, these human frozen samples derived from peripheral blood cannot be grown in a cell culture system. Although we did not perform metabolic analysis for other AMKL cell lines, we did validate in our unpublished studies that PRMT1 drives down CPT1A expression in normal bone marrow cells and platelets in mice and in human leukemia cell line called MEG-01, which can be differentiated into megakaryocytes upon PMA (phorbol 12-myristate 13-acetate) treatment. Therefore, we expect that the PRMT1-mediated metabolic reprogramming we described here should apply to other types of hematological malignancies.

      (2) The observed heterogeneity in Prmt1 expression is noted but not further investigated, leaving gaps in understanding its broader implications.

      The expression level of PRMT1 is heterogeneous within leukemia cell populations, making it intriguing to study. We can sort the cells based on high versus low PRMT1 expression using a fluorescent dye called E84. However, we have not conducted transcriptome analysis on these two populations, mainly due to resource constraints. Theoretically, the E84 high-expression population may transiently utilize glucose more efficiently, as these cells do not ectopically express PRMT1. Therefore, when nutrient levels decline, these cells might switch to the low PRMT1 expression population. It will be interesting to see whether endogenous leukemia cells transiently expressing high levels of PRMT1 take advantage of their efficient usage of glucose and thus adapt to the niche environment successfully, as we observed in the Figure 1. I agree that this would be an interesting direction to pursue in the future.

      (3) Some figures and figure legends didn't include important details or had not matching information.

      We would like to thank the reviewer for pointing out these mistakes. Now we have corrected.

      (4) Some wording is not accurate, such as line 80 "the elevated level of PRMT1 maintains the leukemic stem cells", the study is using the cell line, not leukemia stem cells.

      Leukemic stem cells are often referred to as cells that can initiate leukemia when transplanted into recipient mice, a concept first proposed by John Dick. In this study, we found that even the 6133 cell line displays heterogeneity in terms of PRMT1 expression levels. We identified a subgroup of 6133 cells as leukemia stem cells due to their ability to initiate leukemia.

      (5) In the disease model, histopathology of blood, spleen, and BM should be shown.

      We did not conduct histopathology analysis. 6133 cells associated histopathology has been published in Mercher et al JCI 2009 and a recent preprint by Diane Krause’s group.

      (6) Can MS023 treatment reverse the metabolic changes in PRMT1 overexpression AMKL cells?

      Yes, We demonstrated in figure 4 in the seahorse assays that prmt1 inhibitor can increase the oxygen consumption.

      It would be helpful to provide a summary graph at the end of the manuscript.

      Yes, we now provide a graphic abstract.

      Reviewer #2 (Public review):

      We would like to thank the reviewer for finding the manuscript novel and important.

      Weaknesses:

      (1) The manuscript lacks detailed molecular mechanisms underlying PRMT1 overexpression, particularly its role in enhancing survival and metabolic reprogramming via upregulated glycolysis and diminished oxidative phosphorylation (OxPhos). The findings primarily report phenomena without exploring the reasons behind these changes.

      In the introduction, we highlighted that numerous studies have demonstrated how PMT1 directly interacts with several key enzymes involved in glycolysis. These studies provide a mechanism for the observed upregulation of PMT1 in leukemia. Additionally, our previous research published in eLife 2015 {Zhang, 2015 #5031} demonstrated that PRMT1 methylates the RNA-binding protein RBM15, which can bind to the 3' UTR of mRNAs encoding various metabolic enzymes. Therefore, we propose that PMT1 may also regulate metabolism indirectly through the RBM15 protein.

      (2) The article shows that PRMT1 overexpression leads to augmented glycolysis and low reliance on the OxPhos. However, the manuscript also shows that PMRT1 overexpression leads to increased mitochondrial number and mitochondrial DNA content and has an elevated NADPH/NAD+ ratio. Further, these overexpressing cells have the ability to better survive on alternative energy sources in the absence of glucose compared to low PMRT1-expressing parental cells. Surprisingly, the seashores assay in PRMT1 overexpressing cells showed no further enhancement in the ECAR after adding mitochondrial decoupler FCCP, indicating the truncated mitochondrial energetics. These results are contradicting and need a more detailed explanation in the discussion.

      We have explained the metabolic changes in more detail now. Increasing mitochondria number is not equivalent to increasing fatty acid oxidation and oxygen consumption, as the mitochondria have many other functions. PRMT1 only downregulates CPT1A, which is a rate-limiting step for long-chain fatty acid oxidation. The data suggest that PRMT1 promotes the biogenesis of mitochondria maybe via PGC1alpha as published by Stallcup’s group. The seahorse assays were performed in the high concentration of glucose instead of alternative carbon sources.  FCCP treatment under high glucose conditions did not increase the ECR and OCR, which is normal for leukemia cells as shown in other people’s publications {Sriskanthadevan, 2015 #3944}{Kreitz, 2019 #2133}. PRMT1 could dampen the activities of TCA cycle and the electron transportation chain as the proteomic data from our unpublished data and published data {Fong, 2019 #1185} suggested. The elevated NADPH/NAD+ ratio is another indication that glycolysis and anabolism are enhanced by PRMT1.

      (3) How was disease penetrance established following the 6133/PRMT1 transplant before MS023 treatment?

      Yes, the data was in figure 1f, demonstrating that the penetrance is 100%.  

      (4) The 6133/PRMT1 cells show elevated glycolysis compared to parental 6133; why did the author choose the 6133 cells for treatment with the MS023 and ECAR assay (Fig.3 b)? The same is confusing with OCR after inhibitor treatment in 6133 cells; the figure legend and results section description are inconsistent.

      Sorry for the mistakes while we are preparing the manuscript.  We used 6133/PRMT1 cells to be treated with MS023 in figure 4.

      (5) The discussion is too brief and incoherent and does not adequately address key findings. A comprehensive rewrite is necessary to improve coherence and depth.

      We agree with the reviewer. Now we added comprehensive review of PRMT1-mediated metabolism. The PRMT1 homolgous in yeast is called hmt1. In yeast, hmt1 is upregulated by glucose and enhance glycolysis. So PRMT1 enhanced glycolysis is a conserved pathway in eukaryocytic cells.

      (6) The materials and methods section lacks a description of statistical analysis, and significance is not indicated in several figures (e.g., Figures 1C, D, F; Figures 2D, E, F, I). Statistical significance must be consistently indicated. The methods section requires more detailed descriptions to enable replication of the study's findings.

      We have added extra details on the methods and statistical analysis for the figures.

      (7) Figures are hazy and unclear. They should be replaced with high-resolution images, ensuring legible text and data.

      We have prepared separate figure files with high resolution.

      (8) Correct the labeling in Figure 2I by removing the redundant "D."

      We would like to thank the reviewer and fixed the figure.

    1. Reviewer #2 (Public review):

      Summary:<br /> In the presented work by Wu et al. the authors investigate the role of the transcription factor Pu.1 in the survival and maintenance of microglia, the tissue resident macrophage population in the brain. To this end they generated a sophisticated new conditional pu.1 allele in zebrafish using CRISPR mediated genome editing which allows visual detection of expression of the mutant allele through a switch from GFP to dsRed after Cre-mediated recombination. Using EdU pulse-chase labelling, they first estimate the daily turnover rate of microglia in the adult zebrafish brain which was found to be higher than rates previously estimated for mice and humans. After conditional deletion of pu.1 in coro1a positive cells, they do not find a difference in microglia number at 2 and 8 days or 1 month post injection of Tamoxifen. However, at 3 month post injection, a strong decrease in mutant microglia could be detected. While no change in microglia number was detected at 1mpi, an increase in apoptotic cells and decreased proliferation as observed. RNA-seq analysis of WT and mutant microglia revealed an upregulation of tp53, which was shown to play a role in the depletion of pu.1 mutant microglia as deletion in tp53-/- mutants did not lead to a decrease in microglia number at 3mpi. Through analysis of microglia number in pU.1 mutants, the authors further show that the depletion of microglia in the conditional mutants is dependent on the presence of WT microglia. To show that the phenomenon is conserved between species, similar experiments were also performed in mice.

      This work expands on previous in vitro studies using primary human microglia. The majority of conclusions are well supported by the data, addition of controls and experimental details would strengthen the conclusions and rigor of the paper.

      Strengths:

      Generation of an elegantly designed conditional pu.1 allele in zebrafish that allows for the visual detection of expression of the knockout allele.<br /> The combination of analysis of pu.1 function in two model systems, zebrafish and mouse, strengthens the conclusions of the paper.<br /> Confirmation of the functional significance of the observed upregulation of tp53 in mutant microglia through double mutant analysis provides some mechanistic insight.

      Weaknesses:

      (1) The presented RNA-Seq analysis of mutant microglia is underpowered and details on how the data was analyzed is missing. Only 9-15 cells were analyzed in total (3 pools of 3-5 cells each). Further the variability in relative gene expression of ccl35b.1, which was used as a quality control and inclusion criterion to define pools consisting of microglia, is extremely high (between ~4 and ~1600, Fig. S7A).

      (2) The authors conclude that the reduction of microglia observed in the adult brain after cKO of pu.1 in the spi-b mutant background is due to apoptosis (Lines 213-215). However, they only provide evidence of apoptosis in 3-5 dpf embryos, a stage at which loss of pu.1 alone does lead to a complete loss of microglia (Fig.2E). A control of pu.1 KI/d839 mutants treated with 4-OHT should be added to show that this effect is indeed dependent on the loss of spi-b. In addition, experiments should be performed to show apoptosis in the adult brain after cKO of pu.1 in spi-b mutants as there seems to be a difference in requirement of pu.1 in embryonic and adult stages.

      Comments on Revised Version (from BRE):

      The authors have elaborated on the details of the RNA-Seq procedure and clarified the distinct phenotypes observed with global versus condition pu.1 knockout. In addition, the authors' proposed collaborative relationship between Pu.1 and Spi-b has been expanded in the revised manuscript. The authors have addressed all the minor concerns raised by the reviewer.

    2. Author response:

      The following is the authors’ response to the original reviews

      Reviewer #1 (Public review):

      Strengths:

      The genetic approaches here for visualizing the recombination status of an endogenous allele are very clever, and by comparing the turnover of wildtype and mutant cells in the same animal the authors can make very convincing arguments about the effect of chronic loss of pu.1. Likely this phenotype would be either very subtle or nonexistent without the point of comparison and competition with the wildtype cells.

      Using multiple species allows for more generalizable results, and shows conservation of the phenomena at play.

      The demonstration of changes to proliferation and cell death in concert with higher expression of tp53 is compelling evidence for the authors' argument.

      Weaknesses:

      This paper is very strong. It would benefit from further investigating the specific relationship between pu.1 and tp53 specifically. Does pu.1 interact with the tp53 locus? Specific molecular analysis of this interaction would strengthen the mechanistic findings.

      We agree with the reviewer’s assessment regarding the significance of the relationship between PU.1 and TP53. To investigate the potential interaction between Pu.1 and Tp53 in zebrafish, we analyzed the promoter region of zebrafish tp53. Indeed, we found three PU.1 binding sites (GAGGAA) on tp53 promoter, which locate on the antisense strand from position -1047 to -1042, -1098 to -1093 and -1423 to -1418 relative to the transcriptional start site (Fig. S10). These potential Pu.1 binding sites indicate a direct interaction between Pu.1 and tp53 locus. Furthermore, a previous study by Tschan et al. (2008) elucidated the mechanism by which PU.1 attenuates the transcriptional activity of the P53 tumor suppressor family through direct binding to the DNA-binding and/or oligomerization domains of p53/p73 proteins. We have also cited this study (Line 399-401) and included all above information in the discussion of the revised manuscript (Line 399-405).

      Reviewer #2 (Public review):

      Strengths:

      Generation of an elegantly designed conditional pu.1 allele in zebrafish that allows for the visual detection of expression of the knockout allele.

      The combination of analysis of pu.1 function in two model systems, zebrafish and mouse, strengthens the conclusions of the paper.

      Confirmation of the functional significance of the observed upregulation of tp53 in mutant microglia through double mutant analysis provides some mechanistic insight.

      Weaknesses:

      (1) The presented RNA-Seq analysis of mutant microglia is underpowered and details on how the data was analyzed are missing. Only 9-15 cells were analyzed in total (3 pools of 3-5 cells each). Further, the variability in relative gene expression of ccl35b.1, which was used as a quality control and inclusion criterion to define pools consisting of microglia, is extremely high (between ~4 and ~1600, Figure S7A).

      We feel sorry for the unclearness of RNAseq procedures and have accordingly added the details about RNA-seq data analysis in the “Material and methods” section (Line 491-501). Briefly, reads were aligned to the zebrafish genome using the STAR package. Original counts were calculated with featureCounts package. Differential expression genes (DEGs) were identified with the DESeq2 package. Owing to the technical challenge of unambiguously distinguishing microglia from dendritic cells (DCs) in brain cell suspensions, we employed a strategy of isolating 3-5 cells per pool and quantifying the relative expression of the microglia-specific marker ccl34b.1 normalized to the DC-specific marker ccl19a.1. This approach aimed to reduce DC contamination in downstream analyses. Across all experimental groups subjected to RNA-seq analysis, the ccl34b.1/ccl19a.1 expression ratios exceeded 5, confirming microglia as the dominant cell population. Nonetheless, residual DC contamination in the RNA-seq data cannot be entirely ruled out. We have discussed this technical constraint in the revised manuscript to ensure methodological transparency (Line 498-501).

      (2) The authors conclude that the reduction of microglia observed in the adult brain after cKO of pu.1 in the spi-b mutant background is due to apoptosis (Lines 213-215). However, they only provide evidence of apoptosis in 3-5 dpf embryos, a stage at which loss of pu.1 alone does lead to a complete loss of microglia (Figure 2E). A control of pu.1 KI/d839 mutants treated with 4-OHT should be added to show that this effect is indeed dependent on the loss of spi-b. In addition, experiments should be performed to show apoptosis in the adult brain after cKO of pu.1 in spi-b mutants as there seems to be a difference in the requirement of pu.1 in embryonic and adult stages.

      We apologize for the omission of data regarding conditional pu.1 knockout alone in the embryos in our manuscript, which may have led to ambiguity. We would like to clarify that conditional pu.1 knockout alone at the embryonic stage does not induce microglial death (Fig S2). Microglial death occurs only in both embryonic and adult brains when Pu.1 is disrupted in the spi-b mutant background. The blebbing morphology of some microglia after pu.1 conditional knockout in adult spi-b mutant indicated microglia undergo apoptosis at both embryonic and adult stages (Figure S4 and Fig. S5). The reviewer’s concern likely arises from the distinct outcomes of global pu.1 knockout (Fig. 2) versus conditional pu.1 ablation (Fig. S2). Global knockout eliminates microglia during early development due to Pu.1’s essential role in myeloid lineage specification. We have included this clarification in the revised manuscript (Line 208-211).

      (3) The number of microglia after pu.1 knockout in zebrafish did only show a significant decrease 3 months after 4-OHT injection, whereas microglia were almost completely depleted already 7 days after injection in mice. This major difference is not discussed in the paper.

      We propose that zebrafish Pu.1 and Spi-b function cooperatively to regulate microglial maintenance, analogous to the role of PU.1 alone in mice. This cooperative mechanism likely explains the observed difference in microglial depletion kinetics between zebrafish and mice following pu.1 conditional knockout. Specifically, the compensatory activity of Spi-b in zebrafish may buffer the immediate loss of Pu.1, whereas in mice, the absence of Spi-b expression in microglia eliminates this redundancy, resulting in rapid microglial depletion. Furthermore, during evolution, SPI-B appears to have acquired lineage-specific roles, becoming absent in microglia. We have included the clarification in the revised manuscript (Line 302-305).

      (4) Data is represented as mean +/-.SEM. Instead of SEM, standard deviation should be shown in all graphs to show the variability of the data. This is especially important for all graphs where individual data points are not shown. It should also be stated in the figure legend if SEM or SD is shown

      We have represented our data as mean ± SD in the revised manuscript.

      Recommendations for the authors:

      Reviewing Editor:

      To further strengthen the manuscript, we ask the authors to address the reviewers' comments through additional experiments where necessary. In cases where certain experiments may be challenging, we encourage the authors to address these concerns within the text, such as by referencing any prior evidence of pu.1 and tp53 interactions or incorporating in silico analyses that support such interaction.

      As suggested, we have performed in-silico analysis of Pu.1 binding sites in zebrafish tp53 promoter and also cited previous paper showing how PU.1 attenuates the transcriptional activity of the P53 tumor suppressor family (Line 399-405).

      Reviewer #1 (Recommendations for the authors):

      It would be useful to investigate the relationship between pu.1 and tp53. The data presented here show that pu.1 deficient cells have higher expression of tp53, but this could be an indirect effect. However, since pu.1 has known DNA binding motifs, it would be worthwhile to investigate if there are any direct interactions between pu.1 and the tp53 locus -- does pu.1 directly bind and repress tp53 expression? This could be directly investigated with Cut & Run or an EMSA.

      The interaction between Pu.1 and Tp53 has been discussed in the public review section.

      The paper would likely also benefit from a more in-depth discussion of the relationship of the zebrafish alleles and their relationship to mammalian Pu.1 -- as presented here, the authors are implicitly arguing that zebrafish pu.1 and spi-b are both more closely related to mammalian Pu.1 than to mammalian Spi-b. A clear argument, perhaps backed up by sequence alignment and homology matching, would help readers, especially those less familiar with zebrafish genome duplications.

      We have conducted detailed sequence alignment in our previous work (Yu et al., 2017, Blood) and found zebrafish Spi-b shares the highest similarity with the mammalian SPI-B among Ets family transcription factors in zebrafish. A unique P/S/T-rich region known to be essential for mammalian SPI-B transactivation activity is present in zebrafish Spi-b. Our data do not support the interpretation that Spi-b is more closely related to mammalian Pu.1 than to Spi-b. Instead, functional compensation between pu.1 and spi-b in microglia maintenance likely reflects their shared role as Ets-family transcriptional regulators, rather than ortholog-driven redundancy.

      Reviewer #2 (Recommendations for the authors):

      (1) The nomenclature of the genes in the SPI family in zebrafish is somewhat confusing as genes were renamed several times. It would make it easier for the reader to understand if in the abstract and the main text, spi-b would be referred to as the zebrafish orthologue of mouse SPI-B (as determined by the authors in previous work) rather than the paralogue of zebrafish pu.1. To clarify which genes were analyzed in both zebrafish and mouse, Gene accession numbers should be added.

      Thanks for the recommendations. We have changed “the paralogue of zebrafish pu.1” to “the orthologue of mouse Spi-b” in the abstract (Line 22) and added gene accession numbers for both zebrafish and mouse gene (Line 105-106 and 301-302).

      (2) Methods RNA-seq: Details on how the aligned reads were analyzed to detect differentially expressed genes are missing and should be added. In addition, a table with read counts, fold changes and adjusted p values should be added.

      We have added details of RNA-seq analysis in the Material and Methods part (Line 491-501). A table generated by Deseq2 has been included as a supplemental file to show read counts, fold changes and adjusted p values (Supplemental file 2).

      (3) Figure 2H: It would be helpful to the reader if the KO splicing would be shown in comparison to WT splicing.

      Thank you for your suggestion. We have added the sequence result between exon 3 and exon 4 of pu.1 from wildtype cDNA to show WT splicing in Figure 2H.

      (4) Legend Figure 5C. Relative expression should be replaced with transcripts per million (TPM).

      We have corrected it in the figure legend of Figure 5C (Line 786-787).

      (5) In Figure S3. the label on the y-axis in panel B is not visible.

      We apologize for the mistake during figures assembling. We have corrected it and now the y-axis is visible.

      (6) In Figure S7B an explanation for the colors in the heat map is missing and should be added.

      Colors represent scaled TPM values. The red color represents high expression while the blue color represents low expression. We have added the information in the figure legend.

      (7) A justification for the use of male mice only should be added or additional experiments in female mice should be performed.

      Female mice were excluded to avoid variability associated with estrous cycle-dependent hormonal changes, which are known to influence microglial behavior (Habib P et al., 2015). We have added a justification in the revised manuscript (Line 547-548).

      (8) The manuscript would benefit from some language editing. A few examples are listed below:

      a) line 97: the rostral blood (RBI) should read the rostral blood island.

      b) line 373 typo: nucleus translocation should read nuclear translocation.

      c) line 393 typo: pu.1-dificent should read pu.1-deficient.

      We apologize for the typos or grammar mistakes in the manuscript. We have checked the manuscript thoroughly and revised those typos or grammar mistakes.

      Reference:

      Tschan MP, Reddy VA, Ress A, Arvidsson G, Fey MF, Torbett BE (2008) PU.1 binding to the p53 family of tumor suppressors impairs their transcriptional activity. Oncogene 27: 3489-93

      Yu T, Guo W, Tian Y, Xu J, Chen J, Li L, Wen Z (2017) Distinct regulatory networks control the development of macrophages of different origins in zebrafish. Blood 129: 509-519

      Habib P, Beyer C (2015) Regulation of brain microglia by female gonadal steroids. J Steroid Biochem Mol Biol 146: 3-14

    1. Author response:

      The following is the authors’ response to the previous reviews

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      Tubert C. et al. investigated the role of dopamine D5 receptors (D5R) and their downstream potassium channel, Kv1, in the striatal cholinergic neuron pause response induced by thalamic excitatory input. Using slice electrophysiological analysis combined with pharmacological approaches, the authors tested which receptors and channels contribute to the cholinergic interneuron pause response in both control and dyskinetic mice (in the L-DOPA off state). They found that activation of Kv1 was necessary for the pause response, while activation of D5R blocked the pause response in control mice. Furthermore, in the L-DOPA off state of dyskinetic mice, the absence of the pause response was restored by the application of clozapine. The authors claimed that 1) the D5R-Kv1 pathway contributes to the cholinergic interneuron pause response in a phasic dopamine concentration-dependent manner, and 2) clozapine inhibits D5R in the L-DOPA off state, which restores the pause response.

      Strengths

      The electrophysiological and pharmacological approaches used in this study are powerful tools for testing channel properties and functions. The authors' group has well-established these methodologies and analysis pipelines. Indeed, the data presented were robust and reliable.

      Weaknesses:

      Although the paper has strengths in its methodological approaches, there is a significant gap between the presented data and the authors' claims.

      The authors answered the most of concerns I raised. However, the critical issue remains unresolved.

      I am still not convinced by the results presented in Fig. 6 and their interpretation. Since Clozapine acts as an agonist in the absence of an endogenous agonist, it may stimulate the D5R-cAMP-Kv1 pathway. Stimulation of this pathway should abolish the pause response mediated by thalamic stimulation in SCINs, rather than restoring the pause response. Clarification is needed regarding how Clozapine reduces D5R-ligand-independent activity in the absence of dopamine (the endogenous agonist). In addition, the author's argued that D5R antagonist does not work in the absence of dopamine, therefore solely D5R antagonist didn't restore the pause response. However, if D5R-cAMP-Kv1 pathway is already active in L-DOPA off state, why D5R antagonist didn't contribute to inhibition of D5R pathway? Since Clozapine is not D5 specific and Clozapine experiments were not concrete, I recommend testing whether other receptors, such as the D2 receptor, contribute to the Clozapine-induced pause response in the L-DOPA-off state.

      Thank you for the opportunity to clarify this point. It seems there may have been a misunderstanding regarding our proposal about clozapine's mechanism of action. We are not suggesting that clozapine acts as an agonist, but rather as an “inverse agonist”. Unlike classical agonists, inverse agonists produce a pharmacological effect opposite to that of an agonist. Although clozapine is best known for its antagonistic effects on dopamine and serotonin receptors, under conditions where no endogenous agonist is present, it has been shown to reduce the constitutive activity of D1 and D5 receptors (PMID: 24931197). This is explained in lines 240-254 in the Results section.

      In contrast, the prototypical and selective D1/D5 receptor antagonist SCH23390 does not exhibit inverse agonist properties and would not be expected to produce effects in the absence of an agonist (PMID: 7525564). The observation that SCH23390 blocks the effects of clozapine in dopamine-depleted animals strongly supports the idea that clozapine acts through D1/D5 receptors. This is now clarified in lines 257264.

      To further address your comments, we now include a new figure (Figure 6) presenting experiments that show D2-type receptor agonists do not restore the pause response in dyskinetic mice in the off-L-DOPA condition. These results are described in a new subsection of the Results section and discussed in a newly added paragraph in the Discussion (lines 369-380).

      Finally, to exclude a potential contribution of serotonin receptors to clozapine’s effects, we have expanded what is now Figure 7 (formerly Figure 6) to show that clozapine continues to restore the pause response even in the presence of a serotonin receptor antagonist in the bath.

      All these results are further discussed in lines 342-360.

      Reviewer #2 (Public review):

      Summary:

      This manuscript by Tubert et al. presents the role of D5 receptors (D5R) in regulating the striatal cholinergic interneuron (CIN) pause response through D5R-cAMP-Kv1 inhibitory signaling. Their findings provide a compelling model explaining the "on/off" switch of the CIN pause, driven by the distinct dopamine affinities of D2R and D5R. This mechanism, coupled with varying dopamine states, is likely critical for modulating synaptic plasticity in cortico-striatal circuits during motor learning and execution. Furthermore, the study bridges their previous finding of CIN hyperexcitability (Paz et al., Movement Disorder 2022) with the loss of the pause response in LID mice and demonstrates the restore of the pause through D1/D5 inverse agonism.

      Strengths:

      The study presents solid findings, and the writing is logically structured and easy to follow. The experiments are well-designed, properly combining ex vivo electrophysiology recording, optogenetics, and pharmacological treatment to dissect / rule out most, if not all, alternative mechanisms in their model.

      Weaknesses:

      While the manuscript is overall satisfying, one conceptual gap needs to be further addressed or discussed: the potential "imbalance" between D2R and D5R signaling due to the ligand-independent activity of D5R in LID. Given that D2R and D5R oppositely regulate CIN pause responses through cAMP signaling, investigating the role of D2R under LID off L-DOPA (e.g., by applying D2 agonists or antagonists, even together with intracellular cAMP analogs or inhibitors) could provide critical insights. Addressing this aspect would strengthen the manuscript in understanding CIN pause loss under pathological conditions.

      Thank you for your comments. Although our primary focus is on the role of D5 receptors, we have also investigated the effects of two D2-type receptor agonists in dyskinetic mice in the off-L-DOPA condition. We found that neither quinpirole nor sumanirole was able to restore the pause response. These results are presented in Figure 6 and related text in the Results and Discussion sections.

      Understanding why D2 agonists fail to restore the pause response—despite their expected effect of reducing cAMP levels—is an important question that warrants further investigation. Interestingly, previous studies have reported paradoxical effects of D2 receptor stimulation in SCINs in animal models of dystonia (PMID: 16934985, PMID: 21912682), as well as under conditions where the SCIN’s constitutively active integrated stress response is diminished (PMID: 33888613). This is now discussed in lines 369-380.

      Reviewer #3 (Public review):

      Summary:

      Tubert et al. investigate the mechanisms underlying the pause response in striatal cholinergic interneurons (SCINs). The authors demonstrate that optogenetic activation of thalamic axons in the striatum induces burst activity in SCINs, followed by a brief pause in firing. They show that the duration of this pause correlates with the number of elicited action potentials, suggesting a burst-dependent pause mechanism. The authors demonstrated this burst-dependent pause relied on Kv1 channels. The pause is blocked by a SKF81297 and partially by sulpiride and mecamylamine, implicating D1/D5 receptor involvement. The study also shows that the ZD7288 does not reduce the duration of the pause, and that lesioning dopamine neurons abolishes this response, which can be restored by clozapine.

      Weaknesses:

      While this study presents an interesting mechanism for SCIN pausing after burst activity, there are several major concerns that should be addressed:

      (1) Scope of the Mechanism: It is important to clarify that the proposed mechanism may apply specifically to the pause in SCINs following burst activity. The manuscript does not provide clear evidence that this mechanism contributes to the pause response observed in behavioral animals. While the thalamus is crucial for SCIN pauses in behavioral contexts, the exact mechanism remains unclear. Activating thalamic input triggers burst activity in SCINs, leading to a subsequent pause, but this mechanism may not be generalizable across different scenarios. For instance, approximately half of TANs do not exhibit initial excitation but still pause during behavior, suggesting that the burstdependent pause mechanism is unlikely to explain this phenomenon. Furthermore, in behavioral animals, the duration of the pause seems consistent, whereas the proposed mechanism suggests it depends on the prior burst, which is not aligned with in vivo observations. Additionally, many in vivo recordings show that the pause response is a reduction in firing rate, not complete silence, which the mechanism described here does not explain. Please address these in the manuscript.

      Thank you for the opportunity to clarify these points. We acknowledge that the response of SCINs to optogenetic stimulation of thalamic afferents in brain slices represents a model system that may not capture all aspects of TAN responses to behaviorally salient events. Nevertheless, this approach allows us to test mechanistic hypotheses that are difficult to address in behaving animals with current technologies. This is now stated in lines 311-314.

      Importantly, our ex vivo preparation reproduces, for the first time, the loss of TAN responses observed in non-human primates with parkinsonism, enabling investigation of the underlying mechanisms. In line with your suggestion, we have expanded the Discussion (third and fourth paragraphs) to address the sources of variability in pause responses.

      (2) Terminology: The use of "pause response" throughout the manuscript is misleading. The pause induced by thalamic input in brain slices is distinct from the pause observed in behavioral animals. Given the lack of a clear link between these two phenomena in the manuscript, it is essential to use more precise terminology throughout, including in the title, bullet points, and body of the manuscript.

      Thank you for raising this important point. We agree that it is essential to be precise in describing the nature of the pause observed in our ex vivo model. While we believe that readers would recognize from the abstract and methods that our study focuses on a model of the pause response, we understand your concern about potential confusion. In response, we have revised the terminology in the abstract, bullet points, and throughout the manuscript to more clearly reflect that we are describing an ex vivo model of the pause observed in behaving animals.

      (3) Kv1 Blocker Specificity: It is unclear how the authors ruled out the possibility that the Kv1 blocker did not act directly on SCINs. Could there be an indirect effect contributing to the burst-dependent pause?

      Clarification on this point would strengthen the interpretation of the results.

      This issue is addressed in lines 147-150.

      (4) Role of D1 Receptors: While it is well-established that activating thalamic input to SCINs triggers dopamine release, contributing to SCIN pausing (as shown in Figure 3), it would be helpful to assess the extent to which D1 receptors contribute to this burst-dependent pause. This could be achieved by applying the D1 agonist SKF81297 after blocking nAChRs and D2 receptors.

      Figure 3C shows that the D1/D5 receptor antagonist SCH23390 does not modify the pause, while the full D1/D5 agonist SKF81297 abolishes it, indicating that in our slice preparation, baseline dopamine levels are not contributing to the pause through D1/D5 receptor stimulation.

      (5) Clozapine's Mechanism of Action: The restoration of the burst-dependent pause by clozapine following dopamine neuron lesioning is interesting, but clozapine acts on multiple receptors beyond D1 and D5. Although it may be challenging to find a specific D5 antagonist or inverse agonist, it would be more accurate to state that clozapine restores the burst-dependent pause without conclusively attributing this effect to D5 receptors.

      As explained in our response to Reviewer #1, the effect of clozapine is blocked by the D1/D5-selective antagonist SCH23390. Additionally, new data presented in Figure 7C show that clozapine's ability to restore the pause response is maintained even in the presence of a broad-spectrum serotonin receptor antagonist. Since SCINs do not significantly express D1 receptors, we believe that these findings strongly support a role for D5 receptors in SCINs.

      Comments on revisions:

      The authors have addressed many of my concerns. However, I remain unconvinced that adding an 'ex vivo' experiment fully resolves the fundamental differences between the burst-dependent pause observed in slices - defined by the duration of a single AHP - and the pause response in CHINs observed in vivo, which may involve contributions from more than one prolonged AHP. In vivo, neurons can still fire action potentials during the pause, albeit at a lower frequency. Moreover, in behaving animals, pause duration does not vary with or without initial excitation. The mechanism proposed demonstrates that the pause duration, defined by the length of a single AHP, is positively correlated with preceding burst activity.

      As discussed in paragraphs 3 and 4 of the Discussion (starting at line 285), and illustrated in Figure 1J–K, our data show that the duration of the pause can be modulated by rebound excitation from thalamic input. The absence of this rebound allows us to observe a longer pause when more spikes are elicited during the initial excitatory phase, providing a clearer readout of the contribution of intrinsic membrane mechanisms. We do not claim that intrinsic mechanisms alone account for the entire phasic response of SCINs in behaving animals (lines 295-303 in Discussion).

      To improve clarity, I recommend using the term 'SCIN pause' to describe the ex vivo findings, distinguishing them more explicitly from the 'pause response' observed in behaving animals. This distinction would help contextualize the ex vivo findings as potentially contributing to, but not fully representing, the pause response in vivo.

      We did changes in the abstract, bullet points, and main text to clarify that we are not studying the in vivo response.

      Again, it would be helpful to present raw data for pause durations rather than relying solely on ratios. This approach would provide the audience with a clearer understanding of the absolute duration of the burst-dependent pause and allow for better comparison to the ~200 ms pause observed in behaving animals.

      Thank you for your comment. Following your suggestion, we provide the average pause durations for the data shown in Figure 1H (lines 127–130). We opted not to include raw pause durations in the main text for all figures, as this would make the manuscript more difficult to read and, in our view, is unnecessary. The figures already allow readers to estimate absolute durations: in each case, pause durations are shown relative to baseline ISIs in one panel, while the corresponding absolute ISIs are shown side-by-side. This provides a clearer understanding of pause magnitude relative to the cell’s spontaneous firing, which is more informative than absolute values alone, since one would expect a pause to be longer than the average ISI. Please note that baseline ISI are significantly shorter in dyskinetic mice (Figure 5l). Showing the pause duration relative to baseline ISI allows readers to readily compare results across figures regardless of changes in SCIN baseline firing rate.

      Additionally, it is important to note that, in vivo, pause durations are typically inferred from perievent time histograms (PETHs), which represent population averages across many trials. In contrast, in our ex vivo studies, we measured pause duration on a trial-by-trial basis. This approach enables us to analyze how the pause duration varies as a function of the initial burst size in the same neuron—something not typically reported in in vivo studies. As described in the first two paragraphs of the Results, the same SCIN may respond with a different number of spikes in successive trials, and this variability is influenced by factors such as the timing of the last spontaneous spike relative to stimulation onset (Figure 1D–F). We are not aware of studies reporting trial-by-trial analyses of pause duration in behaving animals, particularly in relation to the strength of initial excitation. Therefore, while our slice preparation may yield pause durations that are longer than those observed in vivo, direct comparison to PETH-derived pause durations from behaving animals is not straightforward.

    1. Author response:

      The following is the authors’ response to the previous reviews

      We are appreciative of the reviewers’ and editors’ constructive suggestions of manuscript, which have helped us to improve our manuscript. We have made considerable revisions to our details of data analyses.

      The reason that the reviews did not change is that there were really three central points that led to the "incomplete". These were (1) the fact that there was potentially a selection bias due to double dipping, and (2) there was potentially a time-confound due to the lack of counterbalancing (3) There is confusion about how the modeling was done, but it seems like the modelling was of the complete block (rather than tied to specific events in that block).

      (1) Double dipping

      We appreciate the opportunity to explain our robust safeguards against double-dipping and have provided detailed clarifications regarding the data analyses (pp.11-14).Our study ensures statistical independence between task-related region selection and hypothesis testing through three orthogonal mechanisms:

      (1) Regressor Orthogonality:Statistical Independence Between Selection and Testing

      The selection regressor (group mean activation) was mathematically independent from test regressors (group differences, behavioral scores). This was confirmed through our GLM implementation: First-level: Task vs. rest contrast (β values) for each participant; Second-level: One-sample t-tests (selection) vs. independent group/behavioral tests.

      (2) Multimodal Validation: Complementary Neural and Behavioral Measures

      We employed multiple distinct metrics to provide convergent yet independent validation of effects.

      Neural Measures: Three orthogonal indices assessed different neural dimensions.

      A. Single-brain activation examines neural activity patterns within individual decision-makers,

      B. while within-group neural synchronization (GNS) quantifies the temporal alignment of neural activity across interacting group members during shared decision processes.

      C. Functional connectivity (FC) analyses, by contrast, measure correlated activity between different brain regions within individual participants.

      Behavioral Safeguards: Behavioral metrics were analyzed in independent regressions, avoiding circularity.

      A. Individual performance was based on personal accuracy,

      B. collective performance represented the group-level average accuracy across raters, and

      C. their similarity was quantified as the Euclidean distance between individual and collective scores.

      (3) Statistical Safeguards

      We further ensured independence by applying strict FDR correction at both selection (p < 0.05) and testing stages (p < 0.05). Besides, permutation test was conducted, we tested 1,000 pseudo-group iterations for GNS null distributions.

      Drawing on both classic and latest NIRS (e.g., Jiang et al., 2015; Liu et al., 2023; Stolk et al., 2016; Xie et al., 2023) and NIRS hyperscanning studies (e.g., Liu et al., 2019; P’arnamets et al., 2020; Reinero et al., 2021; Számadó et al., 2021; Solansky, 2011), we performed the data analyses. Below, we provide the details of our data analysis:

      Single-brain activation. To identify task-related brain regions (channels), we used a one-sample t-test based on brain activation data from all participants during the task compared to the baseline (resting state).

      (1)  Data Collection: Each participant had brain activation data (HbO signals measured by fNIRS) during the task (the entire process of reading, sharing, discussing, and decision-making) and the resting state (baseline).

      (2)  Pre-processing: We sought to explore the neural mechanisms that manipulated group identification and its effect on collective performance. Data were preprocessed using the Homer2 package in MATLAB 2020b (Mathworks Inc., Natick, MA, USA). First, motion artifacts were detected and corrected using a discrete wavelet transformation filter procedure. After that, the raw intensity data were converted to optical density (OD) changes. Then, kurtosis-based wavelet filtering (Wav Kurt) was applied to remove motion artifacts with a kurtosis threshold of 3.3 (Chiarelli, Maclin, Fabiani, & Gratton, 2015). Based on a prior multi-brain study of social interactions (Cheng et al., 2022), the output was bandpass filtered using a Butterworth filter with order 5 and cut-offs at 0.01 and 0.5 Hz to remove longitudinal signal drift and instrument noise. Finally, OD data were converted to HbO concentrations.

      (3) Individual-Level Analysis: First, a GLM was used to compute the "task vs. rest" brain activation contrast for each participant [0,1], obtaining each individual's "task effect" value (β value, representing task activation strength).

      (4) Group-Level Analysis: These "task effect" values from all participants were then aggregated, and a one-sample t-test was performed for each brain region (or channel) to determine whether the average activation in that region was significantly greater than 0 (i.e., significantly more active during the task compared to the resting state).

      (5) Task-Related Regions: If the t-test result for a brain region was significant (p < 0.05, FDR-corrected), we considered that region "task-related" and suitable for further analysis.

      (6) Subsequent Tests:

      - Group Comparisons: We examined differences in activation between groups (e.g., high vs. low group identification) using independent t-tests on the same task vs. baseline contrast.

      - Behavioral Correlations: We analyzed relationships between task-related activation (β values) and behavioral scores (e.g., individual performance) using Pearson analyses.

      - Mediation model: We examined the relationship between an individual's perceived group identification and individual performance, which was mediated by task-related activation (β values).

      Within-Group Neural Synchronization (GNS).

      (1) Data Collection and Pre-processing as above

      (2) Calculation: WTC was applied to generate the brain-to-brain coupling of each pair in each triad (Coherence1&2, Coherence 1&3, and Coherence 2&3). Then, three coherence values from three pairs were averaged as the GNS for each triad, that is, GNS = (Coherence 1&2 + Coherence 1&3 + Coherence 2&3) / 3.

      (3) Task-Related Regions: Time-averaged GNS (also averaged across channels in each group) was compared between the baseline session (i.e., the resting phase) and the task session (from reading information to making decisions) using a series of one-sample t-tests. When determining the frequency band of interest, the time-averaged GNS was also averaged across channels. After that, we analyzed the time-averaged GNS of each channel. Then, channels showing significant GNS were regarded as regions of interest and included in subsequent analyses.

      (4) Permutation test: The nonparametric permutation test was conducted on the observed interaction effects on GNS of the real group against the 1,000 permutation samples.

      (5) Subsequent Tests:

      - Group Comparisons: We examined differences in activation between groups (e.g., high vs. low group identification) using independent t-tests on the same task vs. baseline contrast.

      - Behavioral Correlations: The Pearson’s correlation between GNS and collective performance (i.e., calculated by averaging the individual scores assigned by the three raters for each group) was performed.

      -  Mediation model: We examined how GNS mediated the relationship between group identification and collective performance.

      The brain activation connectivity.

      (1) Data Collection and Pre-processing as above

      (2) Calculation: Exploratory Pearson’s correlations between individual performance related HbO and collective performance-related HbO.

      (3) Moderation analysis: Single-brain activation × connectivity → GNS.

      (2) Counterbalancing.

      We sincerely appreciate this valuable methodological insight. Building on prior group decision-making research (De Wilde et al., 2017; Stasser et al., 1992), we refined all stages to enhance experimental control and procedural clarity throughout the process (i.e., a. Reading information, b. Sharing private information, c. Discussing information, d. Decision) (Xie et al., 2023). Importantly, we maintained a fixed task sequence to preserve ecological validity, as this progression mirrors natural group decision-making dynamics.

      While this design choice precludes sequential counterbalancing, several factors mitigate potential temporal confounds: (1) random assignment and uniform task timing across conditions minimize systematic between-group differences; (2) our whole-block GLM approach captures sustained decision-related neural activity rather than phase-specific effects; and (3) We fully acknowledge this limitation and will incorporate a detailed discussion of temporal considerations in the revised manuscript, while noting that our design provides unique advantages for studying naturalistic decision-making processes.

      (3) The modelling was of the complete block

      In our revised manuscript, we have explicitly stated that the analysis was performed at the block level rather than the event level, for the following reasons:

      (1) The hidden profile task is inherently a “group decision-making process” that unfolds dynamically across multiple stages (reading, sharing, discussing, and deciding). Prior research in this paradigm (De Wilde et al., 2017; Stasser & Titus, 1985; Xie et al., 2023) has consistently treated these phases as integrated blocks because the key cognitive and social processes (e.g., information integration, deliberation, and consensus formation) occur over extended interactions rather than discrete events.

      (2) Methodologically, our fNIRS hyperscanning approach requires longer blocks to reliably capture the slow hemodynamic response and the gradual emergence of inter-brain neural synchronization during naturalistic social exchanges (Cui et al., 2012; Liu et al., 2019). Event-related designs, while useful for transient stimuli, are less suited for studying prolonged, interactive decision-making where neural coupling develops over time. Thus, our block-based analysis aligns with both the cognitive demands of the task and the neuroimaging constraints, ensuring robust detection of group-level neural dynamics.

    1. Reviewer #1 (Public review):

      The authors build on their previous study that showed the midgut microbiome does not oscillate in Drosophila. Here, they focus on metabolites and find that these rhythms are in fact microbiome-dependent. Tests of time-restricted feeding, a clock gene mutant, and diet reveal additional regulatory roles for factors that dictate the timing and rhythmicity of metabolites. The study is well-written and straightforward, adding to a growing body of literature that shows the time of food consumption affects microbial metabolism which in turn could affect the host.

      Some additional questions and considerations remain:

      (1) The main finding that the microbiome promotes metabolite rhythms is very interesting. Which microbiota are likely to be responsible for these effects? Future work could be done to link specific microbiota linked to some of the metabolic pathways investigated.

      (2) TF increases the number of rhythmic metabolites in both microbiome-containing and abiotic flies. This is somewhat surprising given that flies typically eat during the daytime rather than at night, very similar to TF conditions. Future work could be done to restrict feeding to other times of day to see if there is a subsequent shift in the timing of metabolites.

      (3) Along these lines, the authors show that Per loss of function reveals a change in the phase of rhythmic metabolites. The authors note that these changes are not due to altered daily feeding rhythms in per mutants. This data suggest Per itself is responsible for these changes. Future work could be done to characterize the mechanisms responsible for these effects.

      (4) The calorie content of each diet - normal vs high protein vs high-sugar are different. Future work in this area could consider the possibility of a calorie effect rather than difference in nutrition (protein/carbohydrate) or an effect of high protein/sugar on the microbiome itself.

      (5) The supplementary table provided outlining the specific metabolites will be useful for future research in this area.

    2. Author response:

      The following is the authors’ response to the original reviews

      Public Reviews:

      Reviewer #1 (Public Review):

      The authors build on their previous study that showed the midgut microbiome does not oscillate in Drosophila. Here, they focus on metabolites and find that these rhythms are in fact microbiome-dependent. Tests of time-restricted feeding, a clock gene mutant, and diet reveal additional regulatory roles for factors that dictate the timing and rhythmicity of metabolites. The study is well-written and straightforward, adding to a growing body of literature that shows the time of food consumption affects microbial metabolism which in turn could affect the host.

      We thank the reviewer for the positive comments.

      Some additional questions and considerations remain:

      (1) The main finding that the microbiome promotes metabolite rhythms is very interesting. Which microbiota are likely to be responsible for these effects? The author's previous work in this area may shed light on this question. Are specific microbiota linked to some of the metabolic pathways investigated in Figure 5?

      This is a good question. Although the Drosophila microbiome shows limited diversity, comprised largely of two major families (Acetobacteraceae and Lactobacillaceae), effects on the host could arise from just a subset of species within these families. However, identifying these would require inoculating microbiome-free flies with single and mixed combinations of species and conducting metabolomics to examine cycling of each of the three categories of metabolites we studied-- primary, lipids and biogenic amines (each of these may respond differently to different species). We believe this is beyond the scope of this manuscript, which is focused on how cycles in these different types of metabolites change in the context of the microbiome, the circadian clock and different diets.

      (2) TF increases the number of rhythmic metabolites in both microbiome-containing and abiotic flies in Figure 1. This is somewhat surprising given that flies typically eat during the daytime rather than at night, very similar to TF conditions. I would have assumed that in a clock-functioning animal, the effect of restricting food availability should not make a huge difference in the time of food consumption, and thus downstream impacts on metabolism and microbiome. Can the authors measure food intake directly to compare the ad-lib vs TF flies to see if there are changes in food intake? Would restricting feeding to other times of day shift the timing of metabolites accordingly?

      Previous studies have indicated that there is no significant difference in food consumption between ad-lib and TF flies (Gill et al., 2015; Villaneuva et al 2019). We also found that the presence of a microbiome does not alter total food consumption when compared with germ-free flies (Zhang et al, 2023, and current manuscript). Though flies primarily feed during the day, some food consumption occurs at night (i.e the feeding rhythm is not tight) and so restricting food to the daytime can increase metabolite cycling. Restricting feeding to other times of day is expected to shift metabolite cycling. We previously showed that this shifts transcript cycling (Xu et al, Cell Metabolism 2011)

      (3) In Figure 2, Per loss of function reveals a change in the phase of rhythmic metabolites. In addition, the effect of the microbiome on these is very different = The per mutants show increased numbers of rhythmic metabolites when the microbiome is absent, unlike the controls. Is it possible that these changes are due to altered daily feeding rhythms in per mutants? Testing the time and amount of food consumed by the per mutant flies would address this question. Would TF in the per mutants rescue their metabolite rhythms and make them resemble clock-functioning controls?

      We previously showed that per<sup>01</sup> flies lose feeding rhythms in DD and LD conditions, but consume a lot more food (Barber et al, 2021). Given that locomotor rhythms are maintained in per<sup>01</sup> in LD (Konopka and Benzer 1971), these rhythms or other rhythms driven by LD cues likely account for the maintenance of metabolite rhythms. And the increased food consumption may contribute to the changes observed. To address the reviewer’s question about the microbiome, we assayed feeding rhythms in per<sup>01</sup> in the absence/presence of a microbiome on the diets that haven’t been tested before (high sugar and high protein diet). Surprisingly, feeding was rhythmic on a high protein diet, regardless of whether a microbiome was present (new Figure S10). On a high sugar diet, feeding appears to be somewhat rhythmic in the presence of a microbiome (although not significant) and not when the microbiome is absent. The same is true in iso31 controls, and in all cases, the phase is the same. Despite the similar effect of the microbiome on feeding rhythms in wild type and per<sup>01</sup>, the effect on cycling is very different. Thus, feeding rhythms do not appear to explain the effects of the microbiome on metabolite cycling in per<sup>01</sup>.

      (4) The calorie content of each diet-normal vs high protein vs high-sugar are different. The possibility of a calorie effect rather than a difference in nutrition (protein/carbohydrate) should be discussed. Another issue worth considering is the effect of high protein/sugar on the microbiome itself. While the microbiome doesn't seem to affect rhythms in the high-protein diet, the high-sugar diet seems highly microbiome-dependent in Supplementary Fig 8C vs D. Does the diet impact the microbiome and thus metabolite rhythmicity downstream?

      Thank you for these good suggestions. We have added to the discussion the possibility that caloric content, rather than nutrition (protein/carbohydrate), affects metabolite cycling in flies fed normal vs. high-protein vs. high-sugar diets. We have also discussed the possibility that effects of different diets on metabolite cycling are mediated by changes in the microbiome. We cite papers that show effects of diet on microbiomes.

      (5) It would be good if a supplementary table was provided outlining the specific metabolites that are shown in the radial plots. It is not clear if the rhythms shown in the figures refer to the same metabolites peaking at the same time, or rather the overall abundance of completely different metabolites. This information would be useful for future research in this area.

      We have added a supplementary Table 1-21 which includes all the raw metabolites.

      Reviewer #2 (Public Review):

      Summary:

      The paper addresses several factors that influence daily changes in concentration of metabolites in the Drosophila melanogaster gut. The authors describe metabolomes extracted from fly guts at four time-points during a 24-hour period, comparing profiles of primary metabolites, lipids, and biogenic amines. The study elucidates that the percentage of metabolites that exhibit a circadian cycle, peak phases of their increased appearance, and the cycling amplitude depends on the combination of factors (microbiome status, composition or timing of the diet, circadian clock genotype). Multiple general conclusions based on the data obtained with modern metabolomics techniques are provided in each part of the article. Descriptive analysis of the data supports the finding that microbiome increases the number of metabolites for which concentration oscillates during the day period. Results of the experiments show that timed feeding significantly enhanced metabolite cycling and changed its phase regardless of the presence of a microbiome. The authors suggest that the host circadian rhythm modifies both metabolite cycling period and the number of such metabolites.

      Strengths:

      The obvious strength of the study is the data on circadian cycling of the detected 843, 4510, and 4330 total primary metabolites, lipids, and biogenic amines respectively in iso31 flies and 623, 2245, and 2791 respective metabolites in per<sup>01</sup> mutants. The comparison of the abundance of these metabolites, their cycling phase, and the ratio of cycling/non-cycling metabolites is well described and illustrated. The conditions tested represent significant experimental interest for contemporary chronobiology: with/without microbiota, wild-type/mutant period gene, ad libitum/time-restricted feeding, and high-sugar/high-protein diet. The authors conclude that the complex interaction between these factors exists, and some metabolic implications of combinations of these factors can be perceived as reminiscent of metabolic implications of another combination ("...the microbiome and time-restricted feeding paradigms can compensate for each other, suggesting that different strategies can be leveraged to serve organismal health"). Enrichment analysis of cycling metabolites leads to an interesting suggestion that oscillation of metabolites related to amino acids is promoted by the absence of microbiota, alteration of circadian clock, and time-restricted feeding. In contrast, association with microbiota induces oscillation of alpha-linolenic acid-related metabolites. These results provide the initial step for hypothesising about functional explanations of the uncovered observations.

      We thank the reviewer for summarizing the contributions made by this manuscript.

      Weaknesses:

      Among the weaknesses of the study, one might point out too generalist interpretations of the results, which propose hypothetical conclusions without their mechanistic proof. The quantitative indices analysed are obviously of particular interest, however are not self-explaining and exhaustive. More specific biological examples would add valuable insights into the results of this study, making conclusions clearer. More specific comments on the weaknesses are listed below:

      (1) The criterion of the percentage of cycling metabolites used for comparisons has its own limitations. It is not clear, whether the cycling metabolites are the same in the guts with/without microbiota, or whether there are totally different groups of metabolites that cycle in each condition. GO enrichment analysis gives only a partial assessment, but is still not quantitative enough.

      Microbiome-containing flies and germ-free flies do share some cycling metabolites. Figure 6 provides GO analysis for the pathways enriched in each condition, and Figure S6 shows quantitative data on the number that overlap between different conditions. We have also expanded discussion of specific cycling groups (e.g. amino acid metabolism) to indicate that different metabolites of the same pathway may cycle under different conditions. In addition, we have added detailed information for all cycling metabolites in Supplemental Tables 1-21.

      (2) The period of cycling data is based on only 4 time points during 24 hours in 4 replicates (>200 guts per replicate) on the fifth day of the experiment (10-12-day-old adults). It does not convincingly prove that these metabolites cycle the following days or more finely within the day. Moreover, it is not clear how peaks in polar histogram plots were detected in between the timepoints of ZT0, ZT6, ZT12, and ZT18.

      We acknowledge these limitations, but note that these experiments are very challenging because of the amount of tissue/guts needed for each data point and the time it takes to dissect each gut. Thus, getting more closely spaced time points is difficult. And we believe the detection of daily peaks with four biological replicates provides good evidence for cycling. The peaks in polar histogram plots are based on the parameter of JTK_adjphase when conducting JTK cycle analysis; as the data are averaged across replicates, the average can sometimes fall in between two assayed time points. Details can be found in the attached Supplementary Tables.

      (3) Average expression and amplitude are analysed for groups of many metabolites, whereas the data on distinct metabolites is hidden behind these general comparisons. This kind of loss of information can be misleading, making interpretation of the mentioned parameters quite complicated for authors and their readers. Probably more particular datasets can be extracted to be discussed more thoroughly, rather than those general descriptions.

      We analyzed groups of metabolites, dividing them into primary metabolites, lipids and biogenic amines, to extract general take-home messages and also to simplify the presentation. Figure 6 demonstrates specific pathways whose cycling is affected in each condition assayed. And Figure S11 shows examples of cycling metabolites under different conditions. To highlight a dataset that is altered under different conditions, we expanded our discussion of amino acid metabolism, and show how the specific metabolites that cycle in this pathway may vary from one condition to another (Figure S11). For more quantitative data on individual metabolites, we now provide supplementary tables that display all the cycling metabolites. These include those uniquely cycling in one group, those shared between both two groups, and those uniquely cycling in the other group.

      (4) The metabolites' preservation is crucial for this type of analysis, and both proper sampling plus normalisation require more attention. More details about measures taken to avoid different degradation rates, different sizes of intestines, and different amounts of microbes inside them will be beneficial for data interpretation.

      We were careful to control for gut size and to preserve the samples so as to minimize degradation (We placed all the fly samples on ice during collection, and the entire dissection process was also conducted on ice. Once the gut sample collection was completed, we immediately transferred the samples to dry ice for storage. After we finished collecting all the samples, we stored them at -80°C). In general, gut sizes varied in the following order: females fed high-protein diets >females fed normal chow diets> female flies fed high-sugar diets. As the metabolomic facility suggested 10mg samples for each biological repeat, we dissected at least 180 female guts from flies fed high-protein diets, 200 female guts from flies fed normal chow diets, and at least 250 female guts from flies fed high-sugar diets. Also, as gut sizes were smaller in sterile flies, relative to microbiome-containing flies, on a high protein diet, we collected 200 guts from sterile flies under these conditions. Finally, the service that conducted the metabolomics (UC Davis) provided three detailed files to describe the extraction process for primary metabolites, lipids, and biogenic amines, respectively. We have submitted these files as supplemental materials in the revised manuscript.

      (5) The data in the article describes formal phenomena, not directly connected with organism physiology. The parameters discussed obviously depend on the behavior of flies. Food consumption, sleep, and locomotor activity could be additionally taken into account.

      These are very interesting suggestions. Previous results indicated that microbiome-containing flies do not change their total food consumption or exhibit changes in feeding rhythms when compared with germ-free flies (Zhang et al., 2023), which indicates that microbiome-mediated metabolite cycling is independent of feeding rhythms. As noted above, we examined the contribution of feeding to metabolite cycling in per<sup>01</sup> flies, and did not see an obvious link. We also assayed feeding rhythms and overall food consumption in wild type under AS and AM conditions and on different diets, and likewise could not account for changes in metabolite cycling based on altered food intake (new Figure S10). We acknowledge that behavior, including locomotor activity and sleep, could indeed influence metabolite cycling. We have added discussion of this.

      (6) Division of metabolites into three classes limits functional discussion of found differences. Since the enrichment analysis provided insights into groups of metabolites of particular interest (for example, amino acid metabolism), a comparison of their cycling characteristics can be shown separately and discussed.

      The intent of this work was to provide an overall account of changes in metabolite cycling that occur under different conditions/diets/genotypes. We have expanded the discussion of amino acid metabolism and show how different metabolites of this pathway cycle under different conditions (Figure S11). We believe that discussion/analysis of other specific groups would be good follow-up studies, which can build upon this work. Detailed datasets about all cycling metabolites are provided in Table S1-12.

      Reviewer #3 (Public Review):

      Summary:

      The authors. sought to quantify the influence of the gut microbiome on metabolite cycling in a Drosophila model with extensive metabolomic profiling over a 24-hour period. The major strength of the work is the production of a large dataset of metabolites that can be the basis for hypothesis generation for more specific experiments. There are several weaknesses that make the conclusions difficult to evaluate. Additional experiments to quantify food intake over time will be required to determine the direct role of the microbiome in metabolite cycling.

      Strengths:

      An extensive metabolomic dataset was collected with treatments designed to determine the influence of the gut microbiome on metabolite circadian cycling.

      Weaknesses:

      (1) The major strength of this study is the extensive metabolomic data, but as far as I can tell, the raw data is not made publicly available to the community. The presentation of highly processed data in the figures further underscores the need to provide the raw data (see comment 3).

      The raw data have been submitted to the public metabolite database. https://www.ebi.ac.uk/metabolights/. (ID: MTBLS8819)

      In addition, the normalized metabolite data have been added in the supplemental materials.

      (2) Feeding times heavily influence the metabolome. The authors use timed feeding to constrain when flies can eat, but there is no measurement of how much they ate and when. That needs to be addressed.

      Since food is the major source of metabolites, the timing of feeding needs to be measured for each of the treatment groups. In the previous paper (Zhang et al 2023 PNAS), the feeding activity of groups of 4 male flies was measured for the wildtype flies. That is not sufficient to determine to what extent feeding controls the metabolic profile of the flies. Additionally, timed feeding opportunities do not equate to the precise time of feeding. They may also result in dietary restriction, leading to the loss of stress resistance in the TF flies. The authors need to measure food consumption over time in the exact conditions under which transcriptomic and metabolomic cycling are measured. I suggest using the EX-Q assay as it is much less effort than the CAFE assay and can be more easily adapted to the rearing conditions of the experiments.

      As noted above, we have now added considerable additional data on feeding and feeding rhythms in microbiome-containing and sterile wild type and per<sup>01</sup> flies on different diets (Figure S10). Our previous study, using the EX-Q assay method, found no differences in either total food consumption or feeding rhythms between microbiome-containing flies and germ-free flies (Zhang et al., 2023). Also, previous work has demonstrated that there is no significant difference in food consumption between ad-lib and TF flies (Villaneuva et al 2019).

      (3) The data on the cycling of metabolites is presented in a heavily analyzed form, making it difficult to evaluate the validity of the findings, particularly when a lack of cycling is detected. The normalization to calculate the change in cycling due to particular treatments is particularly unclear and makes me question whether it is affecting the conclusions. More presentation of the raw data to show when cycling is occurring versus not would help address this concern, as would a more thorough explanation of how the normalization is calculated - the brief description in the methods is not sufficient.

      For instance, the authors state that "timed feeding had less effect on flies containing a microbiome relative to germ-free flies." One alternative interpretation of that result is that both treatments are cycling but that the normalization of one treatment to the other removes the apparent effect. This concern should be straightforward to address by showing the raw data for individual metabolites rather than the group.

      We have added Supplement Table1-21 that includes detailed information on metabolite identity and data processing. Also, we have included the raw data, encompassing all the cycling metabolites, in the Supplement Table1-21.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      (1) The abstract could be rewritten to clarify. I found the last part of the introduction better but struggled to understand the abstract.

      We apologize for this. The abstract was indeed quite dense; we have revised it for clarity.

      (2) Supplementary Figure 8 could be moved to the main text. Since all the comparisons are on one page it is much easier to see the similarities and differences in the conditions tested.

      We have moved Supplementary Figure 8 to main Figure 5.

      (3) The sex and age of the flies used in all experiments should be clarified. The authors mention female guts are collected in the methods (line 111) but it is not clear if this is throughout.

      All guts used in this study were female. We have clarified this in the manuscript.

      Reviewer #2 (Recommendations For The Authors):

      Some minor notes that might be improved:

      (1) The order of obtaining eggs without microbiota might be different (first - bleaching, second - sterilisation with ethanol). Otherwise, it is not clear why dechorionating is needed after sterilisation.

      Protocols for generating axenic flies vary. We used the method Feltzin et al reported in 2019: “For newborn fly embryos (<12 hours). First, cleanse and sterilize any leftover agar from collection plates using 100% ethanol, second, dechorionate the fly embryos with 10% bleach, and then immediately rinse three times in germ-free PBS”.

      (2) References for the resources used might be provided (MetaboAnalyst5.0, JTK_CYCLEv3.1).

      We have added the reference for MetaboAnalyst5.0, JTK_CYCLEv3.1 (Pang et al., 2022)

      (3) References or justification for the chosen composition of the diets might be useful (standard diet, high-protein diet, high-sugar diet).

      We have added the references (Bedont et al, 2021, Morris et al, 2021).

      (4) Justification of the choice of iso31 line and per<sup>01</sup> mutant might be important.

      iso31 is the standard wild type line we use in the laboratory. To understand the role of the endogenous clock in microbiome-mediated metabolite cycling, we chose the classical canonical clock mutant per<sup>01</sup> as this displays fewer non-circadian phenotypes seen. For instance, loss of transcriptional activators of the clock produces additional effects (e.g. hyperactivity), likely because of the effect it has on overall expression of many genes. We have added this explanation to the manuscript.  

      (5) Abbreviation decoding might be introduced when it is used for the first time in the text (line 240 - TM, TS).

      We apologize for this omission and have rectified it. Thanks

      TM (timed feeding microbiome-containing flies)

      TS (timed feeding germ-free flies)

      (6) The term "germ-free" is recommended to be avoided in the context of the paper (germ-free = infertile for animals). It might be replaced with the terms "without microbiota" or "germ-free" for example.

      Given that the reviewer recommends use of the word “germ-free” in the second sentence, we assume that the first sentence was intended to say we should avoid “sterile” (and not “germ-free”). We have edited to “germ-free” in the manuscript.

      (7) When only one diet is assumed, it might be better to say so (line 324 - "the protein diet" instead of "protein diets").

      Sorry, we have edited accordingly.

      (8) Too many speculative conclusions are confusing (line 476 - what does it mean for "just as” - how exactly similar; line 477 - what kind of "compensation"; line 503 - how exactly it is related to "metabolic homeostasis" and to which kind of homeostasis).

      “just as” was not intended to refer to any degree of similarity but only to the fact that amino acid cycling occurs in the absence of a clock, as it does in the absence of a microbiome. We speculate that this “compensates” for something that is normally conferred by the clock and the microbiome, for instance maybe the clock drives cycling of a microbiome component that is important for protein metabolism. In the absence of either the clock or the microbiome, this is compensated for by amino acid cycling. We have clarified in the text.

      We used the term "metabolic homeostasis" to reflect steady maintenance of metabolic health via interaction and modulation of different factors. As in the case of the example given above for amino acid metabolism, a perturbation of one process might produce a change in another to optimize metabolism. We have changed the wording in the text to better convey our message (lines 576-579)

      (9) Particular examples of metabolites might be beneficial for supporting conclusions (a figure which shows, for instance, the specific data on linolenic acid: in which conditions it cycles, in which not, what is the period of cycling, what are the exact expression and JTK_amplitude values).

      All cycling metabolites, including linolenic acid, are now included in the supplemental tables.

      Reviewer #3 (Recommendations For The Authors):

      (1) The level of biological replication is unclear for the metabolomic experiments. I see that 200 guts per sample were collected and 4 repeat samples were made at each timepoint. Are these 4 biological replicates for each treatment (AS, AM, TS, TM) at each timepoint? 5 replicates are standard in metabolomics. Please be more explicit in the methods.

      There are 4 biological replicates for each time point of each of the 4 treatments. The metabolomics service recommended 4-6 replicates, so we prepared 4 replicates for each sample. As noted above, these preparations are quite difficult. We found that in general the biological replicates do not differ significantly from each other.

      (2) Wolbachia can have a significant influence on fly physiology. How was this variable addressed? Were flies checked for Wolbachia?

      All the flies are Wolbachia-free, as in our previous study (Zhang et al., 2023). Initially, we treated the flies with 1 mM kanamycin (11815024, ThermoFisher) to remove bacteria. Afterwards, we repopulated the flies with a Wolbachia-free microbiome containing Lactobacillus and Acetobacter bacteria from a medium previously occupied by other flies.

      (3) In Results section 1, the authors report changes in the percentages of metabolites that are cycling, but no statistical test is presented to show that these changes are indeed significant. The authors need to report statistics on the percentages of cycling metabolites.

      We used statistical tests, specifically JTK cycle, to determine cycling of each metabolite. The P value for cycling of each metabolite in this test is computed on the basis of all the biological replicates and all time points. Metabolites that showed a significant P value contribute to the percent cycling. As a result, there is only one value for the percentage cycling in each condition. Thus, statistical analysis cannot be done.

      (4) The authors report that the species proportions in the gut microbiome don't cycle, but do absolute CFU counts? By many accounts (see e.g. Blum et al 2013 mBio), the gut microbiome in lab flies is what they recently ate from the food. The abundance of bacteria in the gut would then be directly tied to the timing of feeding. Timed feeding should produce oscillations in individual flies, so individual flies should be analyzed.

      We assume the reviewer is suggesting that rhythmic feeding could result in rhythmic abundance of the microbiome, which could contribute to cycling. This is indeed a possibility and one we now discuss in the manuscript. Thanks! Analysis of the gut microbiome in individual flies would require quantitation of CFUs from single guts. We do not believe a single gut would yield enough material.

      (5) Line 252: the ZT9 peak could just be due to feeding and digestion.

      This is possible. We now acknowledge this

      (6) What is the expectation for metabolite cycling in per mutant flies? Shouldn't per mutant flies have no cycling on average? Does the cycling suggest there is an external factor causing cycling?

      Under light-dark conditions, metabolite cycling in per mutant flies may be driven by light: dark cues, either directly or through other light-driven rhythms e,g. locomotor activity is rhythmic in per<sup>01</sup> flies maintained in LD.

      (7) Performing food intake analysis on each of the treatments would provide critical data to address the direct role of the microbiome in metabolite cycling.

      As noted above, we now provide considerable additional data on food intake at different times of day in microbiome-containing and germ-free wild type and per<sup>01</sup> flies on different diets (Figure S11). Overall, our data indicate that food intake or feeding rhythms do not account for the effects we report here.

      (8) Please be more explicit about replication in the methods and figure legends.

      We have added n=4 for each condition in the methods and figure legends.

      (9) There are numerous minor grammatical errors such as incorrect verb tenses and usage of articles. Additional proofreading could correct these.

      Sorry! We have done a thorough proofreading and made corrections.

    1. Reviewer #1 (Public review):

      Summary:

      The study by Wang et al. investigates cardiac electromechanical modeling and simulation techniques, focusing on the calibration and validation of ventricular models according to ASME V&V40 standards. The researchers aim to calibrate model parameters to align with key biomarkers such as QRS duration and left ventricular ejection fraction, and validate the model against independent measurements such as displacement and strain metrics. The authors also examine the impact of parameter variations on deformation, ejection fraction, strains, and other biomarkers. The overarching aim of the study is to give "credibility to the underlying computational electromechanics framework" and to "pave the way towards credible cardiacelectromechanical Digital Twins."

      Strengths:

      (1) The study presents a solid validation strategy for cardiac models based on independent data.

      (2) It integrates electrophysiological, mechanical, and hemodynamic biomarkers for sensitivity analysis and calibration.

      Weaknesses and Limitations:

      (1) Model Assumptions: The study employs simplified modeling assumptions that are not state-of-the-art, e.g.,<br /> a) Isotropic scaling of the mesh to generate an unloaded reference geometry.<br /> b) Simple afterload and preload models that fail to produce physiological results.<br /> c) Simplified epicardial boundary conditions.

      (2) Numerical Framework:<br /> a) The mesh resolution and/or the numerical framework used for the mechanical part appears to suffer from known numerical artifacts (locking effects), leading to overly stiff or inaccurate behavior in finite element analysis. This results in an artificially stiff response to deformation, which is compensated by setting active contraction to ten times the value reported in the literature. The authors attribute this to limitations in using ex vivo tissue measurements to represent in vivo function, although similar issues were not observed in previous works.<br /> b) Further, the authors employ the monodomain model for the simulation of the electrical excitation and relaxation on a relatively coarse grid with an approximate edge length of 1mm. This resolution is known to be insufficient for reliable results in organ-scale electrophysiology modeling.

      (3) Geometrical model and digital twin: The geometrical model, taken from a public cohort and calibrated to an ECG of another individual along with population-averaged values from a databank (UK Biobank), and unrelated measurements from surgical procedures, can hardly be considered a digital twin. Further, validation of the model was then performed against data from yet another cohort.

      (4) Calibration procedure: There are apparent flaws in the calibration procedure, or it is not described in sufficient detail. The authors dedicate significant effort to motivating parameter ranges, but in the end they use mostly other parameters for the calibration process, aiming to maximize left ventricular ejection fraction. It is not clear whether the chosen parameters result in, e.g., physiological calcium traces or calibrated parameters that are within physiological ranges.

      (5) Goodness of fits, e.g., a direct comparison of the measured and the simulated ECG, are not provided to assess calibration quality.

      (6) Due to these limitations and weaknesses, the authors fall short of achieving some of their goals, particularly establishing credibility for the underlying computational framework and in reproducing healthy pressure-volume loops, and in achieving physiological simulations while using physiological or reported ranges for the calibrated parameters.

      For example, a key physiological requirement is that the right and left ventricular stroke volumes are approximately equal in a heart beating at a limit cycle, as the blood pumped by the right ventricle into the pulmonary circulation must match the amount pumped by the left ventricle into the systemic circulation. This balance is not achieved in this study.

      (7) The conclusive claim that "the study paves the way towards credible electromechanical cardiac Digital Twins" is not supported. The model exhibits non-physiological behavior, requires unsupported parameter alterations (such as a 10-fold active stress scaling), and does not represent a digital twin, as model data are drawn from various unrelated, non-patient-specific sources.

      Conclusion:

      Overall, this reviewer considers that the study requires a major revision, including improvements in numerical methods, modeling choices, and checks for physiological behavior. Nevertheless, the provided tables with averaged values from the UK Biobank and the presented validation strategy could be valuable to the research community.

    1. Note d'Information : Évaluation de l'Efficacité des Politiques Éducatives par la Méthode EDP

      Source : Extraits de "Focus n° 114 mai 2025, Efficacité des politiques éducatives : Sources et hypothèses de calcul", Conseil d’analyse économique (CAE).

      Date de publication : Mai 2025

      Auteurs : Maxime Fajeau, Julien Grenet, Emma Laveissière et Orane Leonetti

      Introduction

      Ce document, publié par le Conseil d'analyse économique (CAE), présente la méthodologie et les paramètres utilisés pour calculer les indices d'efficacité des dépenses publiques (EDP) appliqués aux politiques éducatives analysées dans la Note du CAE n° 84.

      L'objectif est de fournir une évaluation rigoureuse et comparable de diverses politiques publiques en mesurant le bénéfice social généré pour chaque euro net investi par l'État.

      Cette approche intègre les effets à long terme, les retours fiscaux et les économies budgétaires potentielles, offrant ainsi un éclairage pour les décisions budgétaires et les arbitrages redistributifs.

      La Méthode EDP (Efficacité des Dépenses Publiques) / MVPF (Marginal Value of Public Funds)

      • Définition : L'EDP est un outil d'évaluation qui mesure le rendement social marginal d'un euro net investi par l'État. Il permet de comparer différentes politiques publiques en fonction de la valeur qu'elles créent pour la société.
      • Champ d'application : Contrairement aux analyses coût-bénéfice classiques, l'EDP met l'accent sur l'efficacité à long terme, en considérant non seulement les coûts budgétaires immédiats mais aussi les effets différés tels que l'augmentation des recettes fiscales ou la réduction des dépenses publiques futures. Il prend en compte les réponses comportementales des bénéficiaires et les externalités fiscales qui en découlent.
      • Utilité : L'EDP éclaire les arbitrages démocratiques en identifiant les interventions socialement les plus rentables, aidant à hiérarchiser les priorités budgétaires et à identifier les politiques potentiellement "autofinancées". Il vise également à renforcer la transparence des choix publics.

      Formule de Calcul de l'Indice EDP

      La formule générale de l'indice EDP est :

      EDP = ΔB / (ΔC – ΔE)

      Où :

      • ΔB : Bénéfice social total pour les bénéficiaires. Exprimé en termes monétaires, il représente les gains futurs (revenus, conditions de vie améliorées, prestations en nature). Dans le cas des politiques éducatives, l'accent est mis sur l'augmentation potentielle des revenus futurs des bénéficiaires grâce à l'amélioration de leur capital humain et de leurs compétences scolaires.
      • ΔC : Coût brut de la politique pour les finances publiques. Inclut toutes les dépenses de mise en œuvre.
      • ΔE : Externalité fiscale générée par la politique. Représente les recettes supplémentaires pour l'État induites par les effets de la politique (salaires plus élevés, réduction des dépenses sociales, etc.).

      Calcul du Bénéfice Social (ΔB)

      Pour les politiques éducatives, ΔB est principalement basé sur les gains de revenus futurs.

      Il est calculé comme suit :

      ΔB = θ ⋅ δ ⋅ (1 – τ) ⋅ we

      Où :

      • θ : Impact sur les compétences scolaires. Gain en pourcentage d'un écart-type sur les performances scolaires induit par la politique. C'est un paramètre clé qui capture l'efficacité pédagogique de l'intervention.
      • δ : Impact des compétences scolaires sur les salaires futurs. Estimé à 9,5 % en France. Ce paramètre lie l'amélioration des compétences à des gains de revenus sur le marché du travail.
      • τ : Taux marginal moyen d'imposition hors cotisation retraite. Le taux global de prélèvements (impôt sur le revenu, cotisations sociales hors retraite) appliqué au salaire super-brut. Estimé à 39,27 %. Ce taux détermine la part des gains salariaux qui revient à l'individu après impôts et cotisations sociales (hors retraite).
      • we : Revenus futurs contrefactuels actualisés. Les revenus que les bénéficiaires auraient perçus tout au long de leur vie active en l'absence de la politique, actualisés à l'âge d'exposition à l'intervention. L'âge d'exposition a un impact significatif sur les effets cumulatifs, en particulier dans l'éducation. Le taux d'actualisation utilisé est généralement de 3 %.

      Calcul de l'Externalité Fiscale (ΔE)

      L'externalité fiscale est calculée à l'aide des mêmes paramètres que ΔB, en se concentrant sur la part des gains salariaux qui revient à l'État :

      ΔE = θ ⋅ δ ⋅ τ ⋅ we

      Interprétation de l'Indice EDP

      L'EDP prend une large gamme de valeurs, dont les seuils ont une signification spécifique :

      • EDP < 0 : La politique réduit le bien-être des bénéficiaires et génère un coût pour l'État. Intervention coûteuse et dommageable.
      • 0 < EDP < 1 : Le bénéfice social est positif mais inférieur au coût net pour l'État. Ces politiques peuvent être justifiées par des considérations de redistribution ou d'équité.
      • EDP > 1 : Le bénéfice social est supérieur au coût net. La politique est rentable pour la collectivité et représente un bon usage des fonds publics.
      • EDP infini : La politique est intégralement autofinancée (coût net nul ou négatif, par exemple grâce aux retours fiscaux). Même avec un bénéfice social modeste, elle améliore le bien-être collectif sans peser sur les finances publiques.

      Synthèse des Indices EDP pour Certaines Politiques Éducatives Évaluées

      Le document présente une synthèse des résultats de l'évaluation de plusieurs politiques éducatives, regroupées en quatre catégories :

      1. Politiques liées à l'organisation de la classe et de la scolarité :

      Diminution de la taille des classes :

      Primaire : EDP infini. Interprétation : Le dédoublement des classes en primaire est autofinancé, l'externalité fiscale étant supérieure au coût. Bénéfices sociaux : +4 538 € par élève. Coût : +2 856 € par élève. Externalité fiscale : +2 934 € par élève.

      • Collège : EDP = 7,7. Interprétation : Chaque euro net dépensé génère un bénéfice social de 7,70 €. Bénéfices sociaux : +3 509 € par élève. Coût : +2 723 € par élève. Externalité fiscale : +2 269 € par élève.

      • Paramètres clés : Impact sur les compétences (θ) :

      Primaire (1,62 % d'un écart-type par élève en moins),

      Collège (0,97 % d'un écart-type par élève en moins).

      Coût d'un enseignant supplémentaire et coûts non salariaux.

      Redoublement :Primaire : EDP = 0. Interprétation : Bénéfice social nul par euro net dépensé. Bénéfices sociaux : 0 € par année redoublée. Coût : +6 389 € par année redoublée. Externalité fiscale : 0 €. * Collège : EDP = -0,4. Interprétation : Bénéfice social négatif (-0,40 €) par euro net dépensé. Bénéfices sociaux : -4 393 € par année redoublée. Coût : +7 279 € par année redoublée. Externalité fiscale : -2 841 €. * Paramètres clés : Impact salarial du redoublement (β) : Primaire (0 %), Collège (-1,5 %). Coût d'une année de scolarité par élève.

      2. Politiques centrées sur les élèves :

      Tutorat :

      EDP infini, quel que soit le profil du tuteur. Interprétation : Le dispositif est autofinancé, générant une externalité fiscale supérieure à son coût direct. * Bénéfices sociaux (par élève et par an) : Enseignants (+13 507 €), Paraprofessionnels (+10 806 €), Non-professionnels (+5 673 €). * Coût de déploiement (par élève et par an) : Enseignants (+2 981 €), Paraprofessionnels (+874 €), Non-professionnels (0 €). * Externalité fiscale (par élève et par an) : Enseignants (+8 734 €), Paraprofessionnels (+6 987 €), Non-professionnels (+3 668 €). * Paramètres clés : Impact sur les compétences (θ) basé sur une méta-analyse (Enseignants : +50 % d'un écart-type, Paraprofessionnels : +40 %, Non-professionnels : +21 %). Coût horaire du tuteur et volume horaire. * Simulation : Tutorat pour les 10 % des élèves les plus en difficulté :EDP infini. Interprétation : Le dispositif est autofinancé. Bénéfices sociaux : +10 185 € par élève. Coût : +291 € par élève. Externalité fiscale : +6 586 € par élève. * Paramètres clés : Impact sur les compétences (θ) : +40 % d'un écart-type. Coût horaire des tuteurs (rémunérés au salaire minimum).

      Dotation en matériel informatique (PC, tablettes) :EDP = 0. Interprétation : Bénéfice social nul par euro net dépensé. Bénéfices sociaux : 0 € par équipement et par élève. Coût : +566 € par équipement et par élève. Externalité fiscale : 0 €. * Paramètres clés : Impact sur les compétences (θ) : 0 %. Coût unitaire de l'équipement. * Outils numériques d'apprentissage adaptatif :Mathématiques : EDP infini. Interprétation : Le dispositif est autofinancé. Bénéfices sociaux : +4 052 € par élève et par an. Coût : +173 € par élève et par an. Externalité fiscale : +2 620 € par élève et par an.

      Compréhension de l'écrit :

      EDP = 0. Interprétation : Bénéfices observés généralement non significatifs. Bénéfices sociaux : 0 € par élève et par an. Coût : +173 € par élève et par an. Externalité fiscale : 0 €. * Paramètres clés : Impact sur les compétences (θ) basé sur une méta-analyse (Mathématiques : +15 % d'un écart-type, Compréhension de l'écrit : 0 %). Coût annuel par élève du logiciel.

      Compétences socio-comportementales (Énergie Jeunes) :

      EDP infini. Interprétation : Le dispositif est autofinancé. Bénéfices sociaux : +1 391 € par élève. Coût : +65 € par élève. Externalité fiscale : +900 € par élève. * Paramètres clés : Impact sur les compétences (θ) : +8,3 % d'un écart-type. Coût par élève du programme.

      3. Politiques liées aux enseignants :

      • Formation continue des enseignants :

      Formation peu intensive : EDP = 0. Interprétation : Aucun bénéfice social net. Bénéfices sociaux : 0 € par élève et par formation. Coût : +133 € par élève et par formation. Externalité fiscale : 0 €.

      • Formation intensive : EDP infini. Interprétation : Peut être autofinancée. Bénéfices sociaux : +3 157 € par élève et par formation. Coût : +619 € par élève et par formation. Externalité fiscale : +2 042 € par élève et par formation.
      • Paramètres clés : Impact sur les compétences (θ) : Peu intensive (0 %), Intensive (+12,4 % d'un écart-type). Coût journalier et durée de la formation.

      Inspections pédagogiques :EDP infini. Interprétation : Le dispositif est autofinancé. Bénéfices sociaux : +1 277 € par élève et par inspection. Coût : entre +14 € et +20 € par élève et par inspection. Externalité fiscale : +826 € par élève et par inspection. * Paramètres clés : Impact sur les compétences (θ) : +4,2 % d'un écart-type sur les résultats en mathématiques. Coût d'une inspection rapporté au nombre d'élèves.

      Valeur ajoutée des enseignants :Coût maximum acceptable pour être autofinancé (pour une amélioration de 10% d'un écart-type de l'efficacité) : ΔC = 71 000 € par enseignant. Interprétation : Tout dispositif coûtant moins que ce montant et permettant une telle amélioration serait autofinancé. Externalité fiscale générée (ΔE) : +71 000 € par enseignant. * Paramètres clés : Amélioration de la valeur ajoutée de l'enseignant (ΔVA) : 10 % d'un écart-type. Impact sur les compétences (θ) : 10 %. Nombre d'élèves sur une carrière.

      4. Politiques liées aux parents :

      Implication des parents (Mallette des parents) :

      EDP infini. Interprétation : Le dispositif est autofinancé. Bénéfices sociaux : +2 309 € par élève. Coût : +8 € par élève.

      Externalité fiscale : +1 493 € par élève. Paramètres clés : Impact sur les compétences (θ) : +8,3 % d'un écart-type. Coût marginal par collège.

      Hypothèses et Paramètres Clés

      Le document insiste sur le fait que l'outil EDP repose sur des hypothèses et nécessite des données empiriques robustes.

      Les paramètres utilisés dans les calculs sont explicités et justifiés par des références à la littérature de recherche, notamment :

      • L'impact des compétences scolaires sur les salaires futurs (δ).
      • La valeur actualisée des salaires futurs (we) en fonction de l'âge d'exposition.
      • Le taux marginal moyen d'imposition (τ).
      • Les coûts spécifiques à chaque politique (coût des enseignants, coût des matériaux, coût des formations, etc.).
      • Les estimations de l'impact des politiques sur les compétences scolaires (θ ou β), souvent basées sur des méta-analyses ou des études expérimentales et quasi-expérimentales.

      Limites et Considérations

      Bien que l'EDP soit un outil puissant pour éclairer la décision publique, il est important de reconnaître ses limites. Comme tout modèle quantitatif, il dépend de la qualité des données et de la validité des hypothèses retenues.

      L'identification causale des effets des politiques est cruciale pour obtenir des résultats fiables. L'EDP ne remplace pas les arbitrages politiques et sociaux, mais fournit une base factuelle pour ces discussions.

      Conclusion

      Ce document du CAE démontre l'application rigoureuse de la méthode EDP pour évaluer l'efficacité économique et sociale des politiques éducatives en France.

      Les résultats préliminaires présentés suggèrent que certaines interventions, telles que

      • la réduction de la taille des classes en primaire,
      • le tutorat,
      • les outils numériques d'apprentissage adaptatif en mathématiques,
      • les inspections pédagogiques et
      • l'implication des parents via des programmes comme "La Mallette des parents",

      pourraient être particulièrement rentables socialement, voire autofinancées.

      À l'inverse, le redoublement et les dotations en matériel informatique non accompagnées de mesures pédagogiques semblent avoir un bénéfice social nul ou négatif selon cette métrique.

      L'utilisation systématique de cet outil permet de constituer une "bibliothèque" d'évaluations comparables, essentielle pour orienter efficacement la dépense publique dans le domaine de l'éducation.

    1. Multivariate predictive models play a crucial role in enhancing our understanding of complex biological systems and in developing innovative, replicable tools for translational medical research. However, the complexity of machine learning methods and extensive data pre-processing and feature engineering pipelines can lead to overfitting and poor generalizability. An unbiased evaluation of predictive models necessitates external validation, which involves testing the finalized model on independent data. Despite its importance, external validation is often neglected in practice due to the associated costs. Here we propose that, for maximal credibility, model discovery and external validation should be separated by the public disclosure (e.g. pre-registration) of feature processing steps and model weights. Furthermore, we introduce a novel approach to optimize the trade-off between efforts spent on training and external validation in such studies. We show on data involving more than 3000 participants from four different datasets that, for any “sample size budget”, the proposed adaptive splitting approach can successfully identify the optimal time to stop model discovery so that predictive performance is maximized without risking a low powered, and thus inconclusive, external validation. The proposed design and splitting approach (implemented in the Python package “AdaptiveSplit”) may contribute to addressing issues of replicability, effect size inflation and generalizability in predictive modeling studies.

      A version of this preprint has been published in the Open Access journal GigaScience (see paper (https://doi.org/10.1093/gigascience/giaf036), where the paper and peer reviews are published openly under a CC-BY 4.0 license.

      Revised 1 version

      Reviewer 1: Qingyu Zhao

      Thank for the authors for the thorough response. The only remaining comment is that some new supplement figures (figures 8-12) are not cited or explained in the main text (maybe I missed it?). Please make sure to discuss these supplement figures in the main text otherwise readers wouldn't know they are there. The response reads "To provide even more insights, we now present the relationship between the internally validated scores at the time of stopping (I_{act}), the corresponding external validation scores and sample sizes, for all 4 datasets in supplementary figures 8-11. The figures show a relatively good correspondence between internally and externally validated performance estimates with all splitting strategies". What insights are given? What do you mean by relatively good correspondence between internal and external performance? All I see in those figures are some normally distributed scatter plots, so it needs better explanation.

      Reviewer 2: Lisa Crossman

      I previously reviewed this MS and all the comments I made were answered in full. I would be pleased to recommend publication. I was fully able to replicate the adaptive split results from the GitHub repo. I have only one comment which is that I received several generated warnings of "RuntimeWarning: divide by zero encountered in scalar divide", and these can also be seen in the Jupyter notebook example.

    2. Multivariate predictive models play a crucial role in enhancing our understanding of complex biological systems and in developing innovative, replicable tools for translational medical research. However, the complexity of machine learning methods and extensive data pre-processing and feature engineering pipelines can lead to overfitting and poor generalizability. An unbiased evaluation of predictive models necessitates external validation, which involves testing the finalized model on independent data. Despite its importance, external validation is often neglected in practice due to the associated costs. Here we propose that, for maximal credibility, model discovery and external validation should be separated by the public disclosure (e.g. pre-registration) of feature processing steps and model weights. Furthermore, we introduce a novel approach to optimize the trade-off between efforts spent on training and external validation in such studies. We show on data involving more than 3000 participants from four different datasets that, for any “sample size budget”, the proposed adaptive splitting approach can successfully identify the optimal time to stop model discovery so that predictive performance is maximized without risking a low powered, and thus inconclusive, external validation. The proposed design and splitting approach (implemented in the Python package “AdaptiveSplit”) may contribute to addressing issues of replicability, effect size inflation and generalizability in predictive modeling studies.

      A version of this preprint has been published in the Open Access journal GigaScience (see paper (https://doi.org/10.1093/gigascience/giaf036), where the paper and peer reviews are published openly under a CC-BY 4.0 license.

      Original version

      Reviewer 1: Qingyu Zhao

      The manuscript discusses an interesting approach that seeks optimal data split for the pre-registration framework. The approach adaptively optimizes the balance between predictive performance of discovery set and sample size of external validation set. The approach is showcased on 4 applications, demonstrating advantage over traditional fixed data split (e.g., 80/20). I generally enjoyed reading the manuscript. I believe pre-registration is one important tool for reproducible ML analysis and the ideology behind the proposed framework (investigating the balance between discovery power and validation power) is urgently needed. My main concerns are all around Fig. 3, which represents the core quantitative analysis but lacks many details.

      1. Fig. 3 is mostly about external validation. What about training? For each n_total, which stopping rule is activated? What is the training accuracy? What does l_act look like? What is \hat{s_total}?
      2. Results section states "the proposed adaptive splitting strategy always provided equally good or better predictive performance than the fixed splitting strategies (as shown by the 95% confidence intervals on Figure 3)". I'm confused by this because the blue curve is often below other methods in accuracy (e.g., comparing with 90/10 split in ABIDE and HCP).
      3. Why does the half split have the lowest accuracy but the highest statistical power?
      4. How was the range of x-axis (n_total) selected? E.g., HCP has 1000 subjects, why was 240-380 chosen for analysis?
      5. The lowest n_total for BCW and IXI is approximately 50. If n_act starts from 10% of n_total, how is it possible to train (nested) cross-validation on 5 samples or so?

      Two other general comments are: 1. How can this be applied to retrospective data or secondary data analysis where the collection is finished? 2. Is there a guidance on the minimum sample size that is required to perform such an auto-split analysis? It is surprising that the authors think the two studies with n=35 and n=38 are good examples of training generalizable ML models. It is generally hard to believe any ML analysis can be done on such low sample sizes with thousands of rs-fMRI features. By the way, I believe n=25 in Kincses 2024 if I read it correctly.

      Reviewer 2: Lisa Crossman

      External validation of machine learning models - registered models and adaptive sample splitting Gallito et al. The Manuscript describes a methodology and algorithm aimed at better choosing a train-test validation split of data for scikit-learn models. A python package, adaptivesplit, was built as part of this MS as a tool for others to use. The package is proposed to be used together with a suggested workflow to integrate an approach invoking registered models as a full design for better prospective modelling studies. Finally, the work is evaluated on four alternative publicly available datasets of health research data and comprehensive results are presented. There is a trade-off in the split between the amount of sample data to be used for training and the amount of data to use for validation. Ideally the content of each must be balanced in order for the trained model to be representative and equally for the validation set to be representative. This manuscript is therefore very timely due to the large increase in the use of AI models and provides important information and methodology.

      This reviewer does not have the specific expertise to provide detailed comments on the statistical rule methods.

      Main Suggested Revision: 1. The Python implementation of the "adaptivesplit" package is described as available on GitHub (Gallitto et al., n.d.). One of the major points of the paper is to provide the python package "adaptivesplit", however, this package does not have a clear hyperlink, and is not found by simple google searches, and it appears is not yet available. It is therefore not possible to evaluate it at present. There is a website found available with a preprint of this MS after further google searches, https://pnilab.github.io/adaptivesplit/ however, adaptive split is here shown as an interactivate jupyter-type notebook example and not as a python library code. Therefore, it is not clear how available the package is for others' use. Can the authors comment on the code availability?

      Minor comments: 1. Apart from the 80:20 Pareto split of train-test data, other splits are commonly used in ratios such as 75:25 (the scikit-learn default split if ratio is unspecified), and 70:30. Also the cross-validation strategy with train-test-validation split 60:20:20, yet these strategies have not been mentioned or included in the figures such as Fig 3. The splits provided in the figure and discussed are 50:50, 80:20 and 90:10 only. Could the authors discuss alternative split ratios?

    1. To truly understand the cancer biology of heterogenous tumors in the context of precision medicine, it is crucial to use analytical methodology capable of capturing the complexities of multiple omics levels, as well as the spatial heterogeneity of cancer tissue. Different molecular imaging techniques, such as mass spectrometry imaging (MSI) and spatial transcriptomics (ST) achieve this goal by spatially detecting metabolites and mRNA, respectively. To take full analytical advantage of such multi-omics data, the individual measurements need to be integrated into one dataset. We present MIIT (Multi-Omics Imaging Integration Toolset), a Python framework for integrating spatially resolved multi-omics data. MIIT’s integration workflow consists of performing a grid projection of spatial omics data, registration of stained serial sections, and mapping of MSI-pixels to the spot resolution of Visium 10x ST data. For the registration of serial sections, we designed GreedyFHist, a registration algorithm based on the Greedy registration tool. We validated GreedyFHist on a dataset of 245 pairs of serial sections and reported an improved registration performance compared to a similar registration algorithm. As a proof of concept, we used MIIT to integrate ST and MSI data on cancer-free tissue from 7 prostate cancer patients and assessed the spot-wise correlation of a gene signature activity for citrate-spermine secretion derived from ST with citrate, spermine, and zinc levels obtained by MSI. We confirmed a significant correlation between gene signature activity and all three metabolites. To conclude, we developed a highly accurate, customizable, computational framework for integrating spatial omics technologies and for registration of serial tissue sections.

      A version of this preprint has been published in the Open Access journal GigaScience (see paper (https://doi.org/10.1093/gigascience/giaf035)), where the paper and peer reviews are published openly under a CC-BY 4.0 license.

      Original Submission Reviewer 1: Hua Zhang

      Wess et al reports a Python framework, MIIT (Multi-Omics Imaging Integration Toolset), for integrating spatially resolved multi-omics data. Multi-omics imaging represents a pivotal approach for systems molecular biology and biomarker discovery. This method introduces a timely and valuable tool to advance the field. However, in my opinion, this paper still has some issues that need to be addressed before consideration for publication. Cancer tissue exhibits significant heterogeneity effects, in this study, different molecular information obtaining from different tissue sections, this means from different cells as the tissue section is 10 um thickness, almost the diameter of the cells. Please height the meaningful of co-registration information if they are obtained from different cell layers. In particular, for the datasets of spatial transcriptomics and MSI, the experiments were conducted on serial sections with an axial sectioning distance of 40 to 100 μm. This means that the mRNA and metabolites originate from different cells, raising questions about how integrating these two datasets can provide meaningful insights. The multi-omics imaging integration toolset is based on the GreedyFHist, a non-rigid registration algorithm, it suggests including more details about this algorithm and highlight the difference comparing to previously reported non-rigid image co-registration algorithm. The author should demonstrate the accuracy of background segmentation, it concerns certain low signal sample area would be removed in the denoising step. What is criterion to define the background region and sample region in the background segmentation.

      In the Method section, more details need to be included in the spatial transcriptomics part, what the spatial resolution of the 10x Genomics was used. As the MALDI resolution is 30 um, how the pixel alignment of the ST and MSI data if their spatial resolution is different. In the MALDI-MSI of prostate tissue, on tissue MS/MS data is missing to confirm the identification of target analytes of citrate, ZnCl3-, and spermine.

      **Reviewer 2: Santhoshi Krishnan **

      Overview: In this paper, the authors present the Multi-Omics Imaging Integration Toolset, which is a python framework for integration multiple spatial omics datatypes. To facilitate this, they also development a registration method (GreedyFHist) for jointly analyzing sequential tissue layers that have undergone different types of staining/phenotyping regimens. The method validation was done on a 244 fresh-frozen prostrate tissue sections. The highly detailed methods and results section is well appreciated and helps fully contextualize the significance of the study. The definitions of study-specific terms mentioned throughout the paper at the beginning are also appreciated. Data and Code Availability: Detailed code, tutorials and associated instructions have been made available for use by the public, which is appreciated. All systems requirements have also been explicitly laid out for ease of installation and use. The workflow examples provided are quite detailed; however, a more extensive codebase with stepwise explanations within the code will be appreciated. Data has not been made available publicly, except for the raw and processed spatial transcriptomics data; however, detailed and explicit instructions have been provided on data access, keeping in mind local regulations. Revisions: Major Revisions: 1. In recent years, a lot of other platforms, both free and paid, tend to support registration across multiple slides. For example, HALO has a registration feature available as well, along with a host of other open-source datatypes. In that regard, how is your platform different? 2. It is mentioned that downscaling occurs during the registration process in order to reduce runtime - how are nuances in features selected as registration landmarks preserved in such a case? 3. How is the fixed image determined in this case? The assumption would be that a standard H&E image is selected for this purpose- is that assumption, correct? 4. The authors have stated and justified their rationale for using the mentioned evaluation metrics in the paper. However, in the general image registration space, metrics such as the dice coefficient and jaccard index are commonly used and accepted. Is there a particular reason why these were not used as well? It would offer a more complete picture for the general user if these metrics were provided as well. 5. The validation of registering distance neighboring sections is quite a valuable contribution, as the authors rightly stated that in many multi-omics experiments, this might be a necessity. However, when looking at tissue sections that are 80-100 microns apart, it is quite likely that the set of cells that one may be looking at on the x-y coordinate system may not be the same at all; in fact, for a highly heterogeneous/flexible piece of tissue, they might be completely different. In such a circumstance, how much value is there in registering these two sections together instead of, say, separately analyzing them and using alternative methods to combine the results downstream? 6. In the proof of concept presented in the paper, the authors mention using ST and MSI data for validating their framework. Have they also investigated ST integration with more commonly available datatypes such as IHC/mIF? 7. The work that the authors have put in to validate the registration and MIIT framework using different approaches (selecting spatially distant slides, integration using augmented/artificial data) is thorough. However, different tissue types bring in their own challenges, and thus validation of this framework on an external dataset would lend more credence to this much needed framework, especially in the era of increased multiomics analyses.

      Minor Revisions: 1. Please ensure all typos/grammatical mistakes are corrected. 2. In the 'preprocessing of stained histology images', can more details be given on the thresholding process? It is also stated that the threshold is manually adjusted for each image if necessary - how is this determination done? 3. The headings/subheadings organizations within sections can be done in a more organized manner, in some parts it was challenging to determine the organization of sections/subsections. 4. Can some more details be given on the landmarks that were identified per image? Could some examples be provided on what these landmarks are, and how they remain consistence across tissue layers? 5. Currently, the way various samples are used for validating the GreedyFHist and MIIT frameworks are listed out in the paper is quite confusing. It would be appreciated if the authors can distinctly mention the number of samples out of the set of samples, and the associated stained slides are used for each. 6. How were the annotations from the 3 annotators cross validated?

    1. Reviewer #1 (Public review):

      The authors investigated the role of the zinc transporter ZIP10 in regulating zinc sparks during fertilization in mice. By utilizing oocyte-specific Zip6 and Zip10 conditional knockout mice, the authors effectively demonstrate the importance of ZIP10 in zinc homeostasis, zinc spark generation, and early embryonic development. The study is overall useful as it identifies ZIP10 as an important component of oocyte processes that support embryo development, thus opening the door for further investigations. While the study provides solid evidence for the requirement of ZIP10 in the regulation of zinc sparks and zinc homeostasis, it falls short of revealing the underlying mechanism of how ZIP10 exerts this important function.

      (1) The zinc transporters the authors are knocking out are expressed in mouse oocytes through follicular development, and the Gdf9-cre driver used means these oocytes were grown in the absence of appropriate Zinc signaling. Thus, it would be difficult to assert that the lack of fertilization associated with zinc sparks is solely responsible for the failure of embryo development. Spindle morphology and other meiotic parameters do not necessarily report oocyte health, so normalcy of these features may not be a strong argument when it comes to metabolic issues.

      (2) While comparing ZIP6 and ZIP10 in the abstract provides context, focusing more on ZIP10 would improve reader comprehension, as ZIP10 is the primary focus of the study. Emphasizing the specific role of ZIP10 will help the reader grasp the core findings more clearly.

      (3) Zinc transporters ZIP6 and ZIP10 are expressed during follicular development, but the biological significance of the observation is not clearly addressed. The authors should investigate whether the ZIP6 and ZIP10 knockout affects follicular development and discuss the potential implications.

      (4) In Figure 3, the zinc fluorescence images are unclear, making it difficult for readers to interpret the data. Including snapshot images of calcium and zinc spikes as part of the main figure would improve clarity. Moreover, adding more comparative statements and a deeper explanation of why Zip10 KO mice exhibit normal calcium oscillations but lack zinc sparks would strengthen the manuscript.

      (5) While the study identifies the role of ZIP10 in zinc spark generation, it lacks a clear mechanistic insight. The topic itself is interesting, but without providing a more detailed explanation of the underlying mechanisms, the study leaves an important gap. Further discussion on the signaling pathways potentially involved in zinc spark regulation would add depth to the findings.

    2. Reviewer #2 (Public review):

      Summary:

      In this important study, the authors examine the role of two zinc uptake transporters, Zip6 and Zip10, which are important during the maturation of oocytes, and are critical for both successful fertilization and early embryogenesis.

      Strengths:

      The authors report that oocytes from Zip10 knockout mice exhibit lower labile zinc content during oocyte maturation, decreased amounts of zinc exocytosis during fertilization, and affect the rate of blastocyst generation in fertilized eggs relative to a control strain. They do not observe these changes in their Zip6 knockout animals. The authors present clear and well-documented results from a broad range of experimental modalities in support of their conclusions.

      Weaknesses:

      (1) The authors' statement that Zip10 is not expressed in the oocyte nuclei (line 252). Furthermore, in that study, ZIP10 was detected in the nuclear/nucleolar positions of oocytes of all follicular stages (Chen et al., 2023), which we did not observe. This is not supported by Figure 1, where some Zip10 signal is apparent in the primordial, primary, and secondary follicle oocytes. This statement should be corrected.

      (2) Based on the FluoZin-3AM data, there appears to be less labile zinc in the Zip10d/d oocyte, eggs, and embryos; however, FluoZin-3AM has a number of well-known artifacts and does not accurately capture the localization of labile zinc pools. The patterns do not correspond to the well-documented zinc-containing cortical vesicles. Another zinc probe, such as ZinPyr-4 or ZincBY-1 should be used to visualize the zinc vesicles and confirm that there is less labile zinc in these locations as well.

      (3) Line 268 The results indicate that ZIP10 is mostly responsible for the uptake of zinc ions in mouse oocytes. The situation seems a bit more complicated given that the differences in labile zinc content between oocytes from the WT and Zip10d/d animals are small (only 20-30 %) and that the zinc spark is diminished but still apparent at a low level in the Zip10d/d oocytes. Clearly, other factors are involved in zinc uptake at these stages. A variety of studies have suggested that Zip6 and Zip10 work together, perhaps even functioning as a heterodimer in some systems. The double KO would address this more clearly, but if it is not available, it might be more prudent to state that Zip10 plays some role in uptake of zinc in mouse oocytes while the role of Zip6 remains uncertain.

      (4) Zip6d/d oocytes did not have changes in labile zinc, nor did the lack of Zip6 have an impact on the zinc spark. However, Figure S1 does show a small amount of detectable Zip6 in the western blot. It is possible that this small amount could compensate for the complete lack of Zip6. Can ZIP6 be found in immunofluorescence of GV oocytes or MII eggs from the Zip6d/d animals? Additionally, it is possible that Zip6's role is only supplementary to that of Zip10. The authors should discuss this possibility. It would also be interesting to see if the Zip6/Zip10 double knockout displays greater defects compared to the Zip10 knockout when considering previous studies.

    1. Reviewer #1 (Public Review):

      Insects, such as bees, are surprisingly good at recognizing visual patterns. How they achieve this challenging task with limited computational resources is not fully understood. Based on the actual bee's behaviour and visual circuit structure, MaBouDi et al. constructed a biologically plausible model where the circuit extracts essential visual features from scanned natural scenes. The model successfully discriminated a variety set of visual patterns as the actual bee does. By implementing a type of Hebb's rule for non-associative learning, an early layer of the model extracted orientational information from natural scenes essential to pattern recognition. Throughout the paper, the authors provided intuitive logic for how the relatively simple circuit could achieve pattern recognition. This work could draw broad attention not only in visual neuroscience but also in computer vision.

      However, there are a number of weaknesses in the manuscript. 1) The authors claim that the model is inspired by micromorphology, yet it does not rigorously follow the detailed anatomy of the insect brain revealed as of now. 2) Some claims sound a bit too strong compared to what the authors demonstrated with the model. For example, when the authors say the model is minimal, the authors simply investigated how many lobula neurons are required for pattern discrimination in the model. However, the manuscript appears to use this to claim that the presented model is the minimal one required for visual tasks. 3) It lacks explanations of what mechanisms in the model could discriminate some patterns but not others, making the descriptions very qualitative. 4) The authors did not provide compelling evidence that the algorithm is particularly tuned to natural scenes.

    2. Author response:

      Reviewer #1 (Public Review):

      Insects, such as bees, are surprisingly good at recognizing visual patterns. How they achieve this challenging task with limited computational resources is not fully understood. Based on the actual bee's behaviour and visual circuit structure, MaBouDi et al. constructed a biologically plausible model where the circuit extracts essential visual features from scanned natural scenes. The model successfully discriminated a variety set of visual patterns as the actual bee does. By implementing a type of Hebb's rule for non-associative learning, an early layer of the model extracted orientational information from natural scenes essential to pattern recognition. Throughout the paper, the authors provided intuitive logic for how the relatively simple circuit could achieve pattern recognition. This work could draw broad attention not only in visual neuroscience but also in computer vision.

      We appreciate your positive feedback.

      However, there are a number of weaknesses in the manuscript. 1) The authors claim that the model is inspired by micromorphology, yet it does not rigorously follow the detailed anatomy of the insect brain revealed as of now. 2) Some claims sound a bit too strong compared to what the authors demonstrated with the model. For example, when the authors say the model is minimal, the authors simply investigated how many lobula neurons are required for pattern discrimination in the model. However, the manuscript appears to use this to claim that the presented model is the minimal one required for visual tasks. 3) It lacks explanations of what mechanisms in the model could discriminate some patterns but not others, making the descriptions very qualitative. 4) The authors did not provide compelling evidence that the algorithm is particularly tuned to natural scenes.

      We appreciate the reviewer's constructive feedback and have revised the manuscript to clarify and strengthen our claims. Below, we address each of the concerns raised:

      (1) The model does not rigorously follow the detailed anatomy of the insect brain

      We acknowledge that our model is an abstraction rather than a direct reproduction of the full micromorphology of the insect brain. The goal of our study was not to replicate every anatomical feature but rather to extract the core computational principles underlying active vision, based on the functional activity of insect brain. Although the recent connectome studies provide detailed structural maps, they do not fully capture the functional dynamics of sensory processing and behavioural outcomes. Our model integrates key neurobiological insights, including the hierarchical structure of the optic lobes, lateral inhibition in the lobula, and non-associative learning mechanisms shaping spatiotemporal receptive fields.

      However, to address this concern, we have revised the introduction and discussion to explicitly acknowledge the model’s level of abstraction and its relationship to the known anatomy of the insect visual system. Furthermore, we highlight future directions in which connectomic data could refine our model.

      (2) Strength of claims regarding minimality of the model

      We appreciate the reviewer’s concern regarding the definition of a "minimal" model. Our intention was not to claim that this model represents the absolute minimal neural architecture for visual learning task but rather that it identifies a minimal set of necessary computational elements that enable pattern discrimination in insects. To clarify this, we have refined the text to ensure that our conclusions about minimality are explicitly tied to the specific constraints and assumptions of our model. For instance, in the revised manuscript, we emphasise that our findings demonstrate how the number of lobula neurons, inhibitory lateral connection, non-associative learning model, affect neural representation and discrimination performance, rather than establishing an absolute lower bound on the complexity required for visual processing in insects.

      (3) Mechanistic explanations for pattern discrimination

      Thank you for highlighting this point. We have conducted a more detailed analysis of the model’s response to different patterns and expanded our discussion of the underlying mechanisms. To address this, we have refined our explanation of how different scanning strategies and temporal integration mechanisms contribute to neural selectivity in the lobula and overall discrimination performance. Specifically:

      - Figure 3 illustrates how the model benefits from generating sparse coding in the visual network, leading to improved performance in pattern recognition tasks.

      - Figure 5 now includes a more detailed explanation of how different scanning strategies influence the selectivity and separability of lobula neuron responses. Additionally, we provide further analysis of why the model successfully discriminates certain patterns (e.g., simple oriented bars) but struggles with more complex spatially structured quadrant-based patterns.

      - We elaborate on how sequential sampling, temporal coding, and lateral inhibition collectively shape neural representations, enabling the model to distinguish between visual stimuli effectively.

      These refinements provide a clearer mechanistic explanation of the model’s strengths and limitations, ensuring a more comprehensive understanding of its function.

      (4) Evidence that the model is tuned to natural scenes

      We have revised the manuscript to provide stronger support for the claim that the model is particularly adapted to natural scenes. Specifically:

      - Figure 3 demonstrates that training on natural images leads to sparse, decorrelated responses in the lobula, a hallmark of efficient coding observed in biological systems.

      - Supplementary Figure 2-1B shows that training with shuffled images fails to produce structured receptive fields, reinforcing that the statistical structure of natural images is crucial for efficient learning.

      - We now explicitly discuss how the receptive fields emerging from non-associative learning align with known orientation-selective responses in insect visual neurons, supporting the idea that the model is optimised for processing natural visual inputs (Figures 3, 6) and discussion section.

      Taken together, these revisions clarify how the model captures fundamental principles of insect vision without making overly strong claims about biological fidelity. We thank the reviewer for these insightful comments; addressing them has significantly strengthened the clarity and depth of our manuscript.

      Reviewer #2 (Public Review):

      This study is inspired by the scanning movements observed in bees when performing visual recognition tasks. It uses a multilayered network, representing stages of processing in the visual lobes (lamina, medulla, lobula), and uses the lobula output as input to a model of associative learning in the mushroom body (MB). The network is first trained with short "scanning" sequences of natural images, in a non-associative adaptation process, and then several experimental paradigms where images are rewarded or punished are simulated, with the output of the MB able to provide the appropriate discriminative decisions (in some but not all cases). The lobula receptive fields formed by the initial adaptation process show spatiotemporal tuning to edges moving at particular orientations and speeds that are comparable to recorded responses of such neurons in the insect brain.

      There are two main limitations to the study in my view. First, although described (caption fig 1) as a model "inspired by the micromorphology" of the insect brain, implying a significant degree of accuracy and detail, there are many arbitrary features (unsupported by current connectomics). For example, the strongly constrained delay line structure from medulla to­ lobula neurons, and the use of a single MB0N that has input synapses that undergo facilitation and decay according to different neuromodulators. Second, while it is reasonable to explore some arbitrary architectural features, given that not everything is yet known about these pathways, the presented work does not sufficiently assess the necessity and sufficiency of the different components, given the repeated claims that this is the "minimal circuit" required for the visual tasks explored.

      We appreciate your feedback and have refined the manuscript to clarify model design choices and address concerns regarding minimality.

      (1) Model Architecture and Functional Simplifications<br /> While our model is inspired by insect visual system, it is not intended as an exact anatomical reconstruction but rather a functional abstraction to uncover key computational principles of active vision and visual learning. The delay-line structure and simplified MBON implementation were deliberate choices to enable spatiotemporal encoding and associative learning without overcomplicating the model. As connectome data alone do not fully reveal functional relationships, our approach serves as a hypothesis-generating tool for future neurobiological studies.

      (2) Necessity and Sufficiency of Model Components<br /> We have removed overstatements about minimality and now clarify that our model represents a functional circuit rather than the absolute minimal configuration. Additionally, we conducted new control experiments assessing the influence of different model components, and further justifying key mechanisms such as spatiotemporal encoding and lateral inhibition.

      For a more detailed discussion of these revisions and improvements, please refer to our response to the Journal, above.

      Regarding the mushroom body (MB) learning model, it is strange that no reference is made to recent models closely tied to connectomic and other data in fruit flies, which suggests separate MBONS encode positive vs. negative value; that learning is not dependent on MB0N activity (so is not STDP); that feedback from MBONs to dopaminergic signalling plays an important role, etc. Possibly the MB of the bee operates in a completely different way to the fly, but the presented model relies on relatively old data about MB function, mostly from insects other than bees (e.g. locust) so its relationship to the increasingly comprehensive understanding emerging for the fly MB needs to be clarified. It is implied that the complex interaction of the differential effects of dopamine and octopamine, as modelled here, are required to learn the more complex visual paradigms, but it is not actually tested if simpler rules might suffice. Also, given previous work on models of view recognition in the MB, inspired by bees and ants, it seems plausible that simply using static 25×25 medulla activity as input to produce sparse activity in the KCs would be sufficient for MB0N output to discriminate the patterns used in training, including the face stimulus. Thus it is not clear whether the spatiotemporal input and the lobula encoding are necessary to solve these tasks.

      Thank you for your suggestion. The primary focus of this study was not to uncover the exact mechanisms of associative learning in the mushroom body (MB) but rather to evaluate the role of lobula output activity in active vision. The associative learning component was included as a simplified mechanism to assess how the spatiotemporal encoding in the lobula contributes to visual pattern learning.

      We conducted a detailed analysis of lobula neuron activity, focusing on sparsity, decorrelation, and selectivity to demonstrate how the visual system extracts compact yet relevant signals before reaching the learning centre (see Figure 5). Theoretical predictions based on these findings suggest that such encoding enhances pattern recognition performance. While selecting this possible associative learning mechanism allowed us to explicitly evaluate this capability, it also facilitated comparison with previous active vision experiments and assessed the influence of different components on bee behaviour.

      We acknowledge that recent Drosophila connectomics studies suggest alternative MB architectures, including separate MBONs encoding positive vs. negative values, learning mechanisms independent of MBON activity, and feedback from MBONs to dopaminergic pathways. However, visual learning mechanisms in the MB remain poorly characterised, especially in bees, where the functional relevance of different MBON configurations is still unclear. The decision to simplify the MB learning process was intentional, allowing us to prioritise model interpretability over anatomical replication.

      These simplifications have been explicitly discussed in the revised manuscript, where we suggest future directions for integrating more biologically detailed MB models to enhance our understanding of active visual learning in insects. For a broader discussion of our rationale for prioritising computational simplifications over direct neurobiological replication, please refer to our response to the Journal, above.

      It is also difficult to interpret the range of results in fig 3. The network sometimes learns well, sometimes just adequately (perhaps comparable to bees), and sometimes fails. The presentation of these results does not seem to identify any coherent pattern underlying success or failure, other than that the ability to generalise seems limited. That is, recognition (in most cases) requires the presentation of exactly the same stimulus in exactly the same way (same scanning pattern, distance and speed). In particular, it is hard to know what to conclude when the network appears able to learn some "complex patterns" (spirals, faces) but fails to learn the apparently simple plus vs. multiplication symbol discrimination if it is trained and tested with a scan passing across the whole pattern instead of just the lower half.

      We acknowledge that the variability in the model’s performance across different tasks and conditions required a clearer explanation. In the revised manuscript, we have analysed the underlying factors influencing success and failure in greater detail and have expanded the discussion on the model’s generalisation limitations.

      To address this, we have conducted new control experiments and deeper analyses, now presented in Figure 5, Figure 6F, which illustrate how scanning conditions impact recognition performance. Specifically, we examine why the model can successfully learn complex patterns (e.g., spirals, faces) but struggles with apparently simpler tasks, such as distinguishing between a plus and multiplication symbol when scanning the entire pattern rather than just the lower half. Our results suggest that spatially constrained scanning enhances discriminability, while whole-pattern scanning reduces selectivity due to weaker and less sparse feature encoding in lobula neurons.

      We have also clarified in the Discussion section that while the model demonstrates robust pattern learning under specific conditions, its ability to generalise remains limited when tested with compex patterns (Figure 6F. Further investigation is needed to explore how adaptive scanning strategies or hierarchical processing might improve generalisation.

      In summary, although it is certainly interesting to explore how active vision (scanning a visual pattern) might affect the encoding of stimuli and the ability to learn to discriminate rewarding stimuli, some claims in the paper need to be tempered or better supported by the demonstration that alternative, equally plausible, models of the visual and mushroom body circuits are not sufficient to solve the given tasks.

      There is limited knowledge in the literature regarding the neural correlates of visual-related plasticity in the mushroom body (MB). The majority of our current understanding of the MB is derived from studies on olfactory learning, particularly in Drosophila, which does not provide sufficient data to directly implement or comprehensively compare alternative models for visual learning.

      However, the primary focus of our study is on active vision and how spatiotemporal signals are encoded in the insect visual system. Rather than aiming to replicate a detailed biological model of MB function, we intentionally employed a simplified associative learning network to investigate how neural activity emerging from our visual processing model can support pattern recognition. This approach also allows us to compare model performance with bee behaviour, drawing on insights from previous experimental work on active vision in bees.

      We now discuss the limitations of our approach and the rationale for selectively incorporating specific neural network components in lines 652-677. Additionally, we have provided further justification (see responses above) for prioritising a simplified model, rather than attempting to mimic a highly detailed, yet currently unverified, alternative learning circuit. These clarifications help ensure that our claims are appropriately tempered while still demonstrating the functional relevance of our model.

      Reviewer #3 (Public Review):

      In this manuscript, the authors use the data collected and observations made on bees' scanning behaviour during visual learning to design a bio-inspired artificial neural network. The network follows the architecture of bees visual systems, where photoreceptors project into the lamina, then the medulla, medulla neurons connect to a set of spiking neurons in the lobula. Lobula neurons project to kenyon cells and then to MBON, which controls reward and punishment. The authors then test the performance of the network in comparison with real bee data, finding it to perform well in all tasks. The paper attempts to reproduce a living organism network with a practical application in mind, and it is quite impressive! I appreciate both the potential implications for the understanding of biological systems and the applications in the development of autonomous agents, making the paper absolutely worth reading.

      Thank you for your positive feedback and appreciation of our work.

      However, I believe that the current version somewhat lacks in clarity regarding the methodology and in some of the keywords used to describe the model.

      Definitions:<br /> Throughout the manuscript, the authors use some key terminology that I believe would benefit from some clarification.<br /> The generated model is described in the title and once in the introduction as "neuromorphic". The model is definitely bio-inspired, but at least in some layers of the neural network, the model is built very differently from actual brain connectivity. Generally, when we use the term neuromorphic we imply many advantages of neural tissue, like energy efficiency, that I am not sure the current model is achieving. I absolutely see how this work is going in that direction, and I also fundamentally agree with the choice of terminology, but this should be clearly explained to not risk over-implications

      We appreciate the reviewer’s feedback and acknowledge the importance of clarifying key terminology in our manuscript. As outlined in our response to the Journal, we intentionally simplified the model to focus on understanding the core computational processes involved in active vision rather than precisely replicating the full complexity of insect neural circuits (see other reasons for simplification in the manuscript). This simplification allows us to systematically analyse the influence of specific components underlying active vision mechanisms.

      Despite these simplifications, our model incorporates key neuromorphic principles, including the use of a recurrent neural network architecture and a spiking neuron model at multiple processing levels. These elements enable biologically inspired information processing, aligning with the fundamental characteristics of neuromorphic computing, even if the model does not explicitly focus on hardware efficiency or energy constraints.

      The authors describe this as a model of "active vision". This is done in the title of the article, and in the many paragraph headings (methods, results). In the introduction, however, the term active vision is reserved to the description of bees' behavior. Indeed, the developed model is not a model of active vision, as this would require for the model to control the movement of the "camera". Here instead the stimuli display is given to the model in a fixed progression. What I suspect is that the authors' aim is to describe a model that supports the bees' active vision, not a model of active vision. I believe this should be very clear from the paper, and it may be appropriate to remove the term from the title.

      While our model does not actively control camera movement in the environment, it does simulate the effects of active vision by incorporating scanning dynamics. Our results demonstrate that model responses change significantly with variations in scanning speed and restricted scanning areas, highlighting the importance of movement in shaping visual encoding. However, we acknowledge that true active vision would involve adaptive, real-time control of gaze or trajectory, which the step after the current implementation for make more realistic model of active vison. To address your concern, we have discussed the potential for incorporating dynamic flight behaviours in future studies, allowing the model to actively adjust its scanning strategy based on learned visual cues.

      In the short title, it said that this network is minimal. This is then characterized in the introduction as the minimal network capable of enabling active vision in bees. The authors, however, in their experiment only vary the number of lobula neurons, without changing other parts of the architecture. Given this, we can only say that 16 lobula neurons is the minimal number required to solve the experimental task with the given model. I don't believe that this is generalizable to bees, nor that this network is minimal, as there may be different architectures (for the other layers especially) that require overall less neurons. Moreover, the tasks attempted in the minimal network experiment did not include any of the complex stimuli presented in figure 3, like faces. It may be that 16 lobula neurons are sufficient for the X vs + and clockwise vs counter-clockwise spirals, but we do not know if increasing stimuli complexity would result in a failure of the model with 16 neurons.

      We agree that analysing only the number of lobula neurons is not sufficient to establish a truly minimal model for active vision. To address this, we conducted further control experiments to evaluate the influence of other key components, including non-associative learning, scanning behaviour, and lateral connectivity, on model performance. Our results suggest that the proposed model represents a computationally minimal network capable of implementing a basic active vision process, but a more complex model would be required for higher-order visual tasks.

      However, to avoid potential misinterpretation, we have revised the short title and updated the manuscript to clarify that our model identifies a possible minimal functional circuit rather than the absolute minimal network for active vision. Additionally, we have added further discussion on the simplifications made in the model and emphasised the need for future studies to explore alternative architectures and assess their relevance for understanding active vision in insects.

      Methodology:

      The current explanation of the model is currently a bit lacking in clarity and details. This risks impacting negatively on the relevance of the whole work which is interesting and worth reading! This issue affects also the interpretation of the results, as it is not clear to what extent each part of the network could affect the results shown. This is especially the case when the network under-performs with respect to the best performing scenario (e.g., when varying the speed and part of the pattern that is observed, such as in Fig 2C). Adding a detailed technical scheme/drawing specific to the network architecture could have been a way of significantly increasing the clarity of the Methods section and the interpretation of the results.<br /> On a similar note, the authors make some comparisons between the model and real bees. However, it remains unclear whether these similarities are actually indicative of an optimality in the bees visual scanning strategy, or just deriving from the authors design. This is for me particularly important in the experiments aimed at finding the best scanning procedure. If the initial model training is based on natural images it is performed by presenting left to right moving frames, the highest efficiency of lower-half scanning may be due to how the weights in the initial layers are structured and a low generalizability of the model, rather than to the strategy optimality

      We appreciate the reviewer’s constructive feedback and have taken steps to enhance the clarity, interpretability, and transparency of our model description and results. Below, we address the concerns regarding model explanation, performance interpretation, and the comparison with real bee behaviour.

      (1) Improved Model Explanation and Network Clarity: We apologise that the previous version of the manuscript did not fully detail the architecture and functioning of the model. To address this, we have expanded the Methods section with a more detailed breakdown of the network components, their roles, and their contribution to active vision processing. Additionally, we have summarised the network architecture and its implementation for visual learning tasks at the beginning of the Results section, providing a clearer overview of the information flow from visual input to associative learning. Furthermore, we have explicitly analysed and discussed the role of key model components, including scanning strategies, lateral connectivity, and non-associative learning mechanisms, clarifying how each contributes to the observed results.

      (2) Interpretation of Model Performance Variability: Understanding the factors influencing performance variability is crucial, and to improve clarity, we have conducted further analysis of model performance across different conditions, particularly examining the effects of scanning speed, spatial constraints, and feature encoding (see Figure 2C). Additionally, we have expanded the discussion on how scanning conditions impact performance, providing explanations for why some conditions lead to higher or lower discrimination success. Furthermore, we have clarified why certain stimuli present greater challenges for the model, linking these difficulties to receptive field properties and scanning dynamics.

      (3) Comparison Between Model Behaviour and Real Bees: To address your concern regarding the link between scanning preferences and true biological optimality, we have included further analysis discussing the influence of training conditions on the model’s learned behaviours. Additionally, we propose future experiments to test alternative scanning strategies, including adaptive scanning mechanisms that adjust based on visual task demands. Furthermore, we have expanded the discussion on the simplifications made in this study, explicitly stating the limitations of the model and emphasising the need for future research to explore more flexible and biologically plausible scanning mechanisms.

      We believe these revisions significantly enhance the clarity and interpretability of the study, ensuring that the model’s findings are well contextualised within both computational and biological frameworks.

    1. Author response:

      The following is the authors’ response to the previous reviews

      Reviewer #1 (Public review):

      Specific comments:

      (1) It is difficult to appreciate that there is a "peripheral sub-membrane microtubule array" as it is not well defined in the manuscript. This reviewer assumes that this is in the respective field clear. Yet, while it is appreciated that there is an increased amount of MTs close to the cytoplasmic membrane, the densities appear very variable along the membrane. Please provide a clear description in the Introduction what is meant with "peripheral sub-membrane microtubule array".

      A definition has been added to the Introduction.

      (2) The authors described a "consistent presence of a significant peripheral array in the C57BL/ 6J control mice, while the KO counterparts exhibited a partial loss of this peripheral bundle.

      Specifically, the measured tubulin intensity at the cell periphery was significantly reduced in the KO mice compared to their wild-type counterparts". In vitro "control cells had convoluted nonradial MTs with a prominent sub-membrane array, typical for β cells (Fig. 2A), KIF5B-depleted cells featured extra-dense MTs in the cell center and sparse receding MTs at the periphery (Fig. 2B,C)". Please comment/discuss why in vivo there are no "extra-dense MTs in the cell center".

      We now add a discussion of this point, which we believe could be a manifestation of 3D shape of a beta cell in tissue and/or compensatory mechanisms in organisms.

      (3) Authors should include in the Discussion a paragraph discussing the fact that small changes in MT configuration can have strong effects.

      A paragraph added to the discussion.

      Recommendations for the authors:

      Reviewer #1 (Recommendations for the authors):

      (1) Figure 1: Even though the reviewer appreciates that minor changes of MT configuration have severe effects, still the overall effects appear minor (40 vs. <50% or 35% vs. around 28%). Notably, there are no statistically significant differences in the different groups in Fig. 1Suppl-Fig.1 D. This reviewer is not sure if the combination of many not significantly different data points can result in significant changes and this should be checked by a statistician. Authors should include in the Discussion a paragraph discussing the fact that small changes in MT configuration can have strong effects.

      We have now added the requested paragraph to the discussion. Indeed, the differences are small, and the significance is only detected in a data set with a large sample size in Fig. 1J,K (combined data sets with smaller sizes from Fig. 1-Suppl-Fig.1 D), consistent with the fact that a larger sample size generally provides more power to detect an effect.

      (2) Unfortunately, the authors cannot block kinesin-1 resulting in microtubule accumulation in the cell center and then release the block (best inhibiting microtubule formation), to show that the MTs accumulated in the cell center will be transported to the periphery.

      This is indeed the case at the moment, yes.

      Minor comments:

      - Abstract: β-cells vs. β cells (and throughout the manuscript)

      - Page 4: "MTOC, the Golgi, (Trogden et al. 2019), and"

      - Page 5: "β-cell specific"

      - MT-sliding vs. MT sliding

      - Kinesin 1 vs. kinesin-1

      - Page 6, line 1: "β cells. actively"

      - Page 7: "a microtubule probe", should be "MT"

      - Page 9: "1μm" vs. "1 μm"

      - Page 10: "demonstrate a dramatic effect" recommended is: "demonstrate a marked effect"

      - Page 13, line 1: dramatically vs. markedly

      - Page 13, line 5: "50μm" vs. "50 μm" (in general, there should be a space between number and unit?)

      - "37 degrees C" vs. "37{degree sign}C"

      - Animal protocol number?

      - "Mice were euthanized by isoflurane inhalation"? What concentration? How long? More details are needed (no cervical dislocation?).

      - Antibodies: more identifiers are needed.

      - Antibody information in Key reagents and under 5. Reagents and antibodies do not fit (1:500 and 1:1000).

      Thank you, we corrected all relevant information now.

    1. Reviewer #2 (Public review):

      Summary:

      In this manuscript, the authors set out to resolve a long-standing mystery in the field of sensory biology - how large, presynaptic bodies called "ribbon synapses" migrate to the basolateral end of hair cells. The ribbon synapse is found in sensory hair cells and photoreceptors, and is a critical structural feature of a readily releasable pool of glutamate that excites postsynaptic afferent neurons. For decades, we have known these structures exist, but the mechanisms that control how ribbon synapses coalesce at the bottom of hair cells is not well understood. The authors addressed this question by leveraging the highly-tractable zebrafish lateral line neuromast, which exhibits a small number of visible hair cells, easily observed in time-lapse imaging. The approach combined genetics, pharmacological manipulations, high-resolution imaging and careful quantifications. The manuscript commences with a developmental time course of ribbon synapse development, characterizing both immature and mature ribbon bodies (defined by position in the hair cell, apical vs. basal). Next, the authors show convincing (and frankly mesmerizing) imaging data of plus end-directed microtubule trafficking toward the basal end of the hair cells, and data highlighting the directed motion of ribbon bodies. The authors then use a series of pharmacological and genetic manipulations showing the role of microtubule stability and one particular kinesin (Kif1aa) in the transport and fusion of ribbon bodies, which is presumably all prerequisite for hair cell synaptic transmission. The data suggest that microtubules and their stability is necessary for normal numbers of mature ribbons, and that Kif1aa is likely required for fusion events associated with ribbon maturation. Overall, the data provide a new and interesting story on ribbon synapse dynamics.

      Strengths:

      (1) The manuscript offers comprehensive Introduction and Discussion sections that will inform generalists and specialists.<br /> (2) The use of Airyscan imaging in living samples to view and measure microtubule and ribbon dynamics in vivo represents a strength. With the rigorous quantification and thoughtful analyses, the authors generate datasets often only gotten in cultured cells or more diminutive animal models (e.g., C. elegans).<br /> (3) The number of biological replicates and the statistical analyses are strong. The combination of pharmacology and genetic manipulations also represents strong rigor.<br /> (4) One of the most important strengths is that the manuscript and data spur on other questions - namely, do (or how do) ribbon bodies attach to Kinesin proteins? Also, and as noted in the Discussion, do hair cell activity and subsequent intracellular calcium rises facilitate ribbon transport/fusion.

    2. Reviewer #3 (Public review):

      Summary:

      The manuscript uses live imaging to study the role of microtubules in the movement of ribeye aggregates in neuromast hair cells in zebrafish. The main findings are that

      (1) Ribeye aggregates, assumed to be ribbon precursors, move in a directed motion toward the active zone;<br /> (2) Disruption of microtubules and kif1aa increases the number of ribeye aggregates and decreases the number of mature synapses.

      The evidence for point 2 is compelling, while the evidence for point 1 is less convincing. In particular, the directed motion conclusion is dependent upon fitting of mean squared displacement that can be prone to error and variance to do stochasticity, which is not accounted for in the analysis. Only a small subset of the aggregates meet this criteria and one wonders whether the focus on this subset misses the bigger picture of what is happening with the majority of spots.

      Strengths:

      (1) The effects of Kif1aa removal and nocodozole on ribbon precursor number and size is convincing and novel.<br /> (2) The live imaging of Ribeye aggregate dynamics provides interesting insight into ribbon formation. The movies showing fusion of ribeye spots are convincing and the demonstrated effects of nocodozole and kif1aa removal on the frequency of these events is novel.<br /> (3) The effect of nocodozole and kif1aa removal on precursor fusion is novel and interesting.<br /> (4) The quality of the data is extremely high and the results are interesting.

      Weaknesses:

      (1) To image ribeye aggregates, the investigators overexpressed Ribeye-a TAGRFP under control of a MyoVI promoter. While it is understandable why they chose to do the experiments this way, expression is not under the same transcriptional regulation as the native protein and some caution is warranted in drawing some conclusions. For example, the reduction in the number of puncta with maturity may partially reflect regulation of the MyoVI promoter with hair cell maturity. Similarly, it is unknown whether overexpression has the potential to saturate binding sites (for example to motors), which could influence mobility. In the revised manuscript, the authors provide evidence to suggest that overexpression is not at unreasonably high levels, which is reasonable. However, I think it remains important to think of these caveats while reading the paper--especially keeping in mind that expression timing is undoubtedly influenced by the transcriptional control of the exogenous promoter .<br /> (2) The examples of punctae colocalizing with microtubules look clear (fig 1 F-G), but the presentation is anecdotal. It would be better and more informative, if quantified.<br /> (3) It appears that any directed transport may be rare. Simply having an alpha >1 is not sufficient to declare movement to be directed (motor driven transport typically has an alpha approaching 2). Due to randomness of a random walk and errors in fits in imperfect data will yield some spread in movement driven by Brownian motion. Many of the tracks in figure 3H look as thought they might be reasonably fit by a straight line (i.e. alpha = 1).<br /> (4) The "directed motion" shown here does not really resemble motor driven transport observed in other systems (axonal transport, for example) even in the subset that have been picked out as examples here. While the role for microtubules and kif1aa in synapse maturation is strong, it seems likely that this role may be something non-canonical (which would be interesting). In the revision, the authors do an excellent job of considering the issues brought up in point 3 and 4. While perhaps no longer a weakness, I am leaving the critiques here for context for the readers to consider. The added taxol results may not completely settle the issue, but are interesting and provide important information.

    3. Author response:

      The following is the authors’ response to the original reviews

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      The manuscript by Hussain and collaborators aims at deciphering the microtubule-dependent ribbon formation in zebrafish hair cells. By using confocal imaging, pharmacology tools, and zebrafish mutants, the group of Katie Kindt convincingly demonstrated that ribbon, the organelle that concentrates glutamate-filled vesicles at the hair cell synapse, originates from the fusion of precursors that move along the microtubule network. This study goes hand in hand with a complementary paper (Voorn et al.) showing similar results in mouse hair cells.

      Strengths:

      This study clearly tracked the dynamics of the microtubules, and those of the microtubule-associated ribbons and demonstrated fusion ribbon events. In addition, the authors have identified the critical role of kinesin Kif1aa in the fusion events. The results are compelling and the images and movies are magnificent.

      Weaknesses:

      The lack of functional data regarding the role of Kif1aa. Although it is difficult to probe and interpret the behavior of zebrafish after nocodazole treatment, I wonder whether deletion of kif1aa in hair cells may result in a functional deficit that could be easily tested in zebrafish?

      We have examined functional deficits in kif1aa mutants in another paper that was recently accepted: David et al. 2024. https://pubmed.ncbi.nlm.nih.gov/39373584/

      In David et al., we found that in addition to a subtle role in ribbon fusion during development, Kif1aa plays a major role in enriching glutamate-filled synaptic vesicles at the presynaptic active zone of mature hair cells. In kif1aa mutants, synaptic vesicles are no longer enriched at the hair cell base, and there is a reduction in the number of synaptic vesicles associated with presynaptic ribbons. Further, we demonstrated that kif1aa mutants also have functional defects including reductions in spontaneous vesicle release (from hair cells) and evoked postsynaptic calcium responses. Behaviorally, kif1aa mutants exhibit impaired rheotaxis, indicating defects in the lateral-line system and an inability to accurately detect water flow. Because our current paper focuses on microtubule-associated ribbon movement and dynamics early in hair-cell development, we have only discussed the effects of Kif1aa directly related to ribbon dynamics during this time window. In our revision, we have referenced this recent work. Currently it is challenging to disentangle how the subtle defects in ribbon formation in kif1aa mutants contribute to the defects we observe in ribbon-synapse function.

      Added to results:

      “Recent work in our lab using this mutant has shown that Kif1aa is responsible for enriching glutamate-filled vesicles at the base of hair cells. In addition this work demonstrated that loss of Kif1aa results in functional defects in mature hair cells including a reduction in evoked post-synaptic calcium responses (David et al., 2024). We hypothesized that Kif1aa may also be playing an earlier role in ribbon formation.”

      Impact:

      The synaptogenesis in the auditory sensory cell remains still elusive. Here, this study indicates that the formation of the synaptic organelle is a dynamic process involving the fusion of presynaptic elements. This study will undoubtedly boost a new line of research aimed at identifying the specific molecular determinants that target ribbon precursors to the synapse and govern the fusion process.

      Reviewer #2 (Public Review):

      Summary:

      In this manuscript, the authors set out to resolve a long-standing mystery in the field of sensory biology - how large, presynaptic bodies called "ribbon synapses" migrate to the basolateral end of hair cells. The ribbon synapse is found in sensory hair cells and photoreceptors, and is a critical structural feature of a readily-releasable pool of glutamate that excites postsynaptic afferent neurons. For decades, we have known these structures exist, but the mechanisms that control how ribbon synapses coalesce at the bottom of hair cells are not well understood. The authors addressed this question by leveraging the highly-tractable zebrafish lateral line neuromast, which exhibits a small number of visible hair cells, easily observed in time-lapse imaging. The approach combined genetics, pharmacological manipulations, high-resolution imaging, and careful quantifications. The manuscript commences with a developmental time course of ribbon synapse development, characterizing both immature and mature ribbon bodies (defined by position in the hair cell, apical vs. basal). Next, the authors show convincing (and frankly mesmerizing) imaging data of plus end-directed microtubule trafficking toward the basal end of the hair cells, and data highlighting the directed motion of ribbon bodies. The authors then use a series of pharmacological and genetic manipulations showing the role of microtubule stability and one particular kinesin (Kif1aa) in the transport and fusion of ribbon bodies, which is presumably a prerequisite for hair cell synaptic transmission. The data suggest that microtubules and their stability are necessary for normal numbers of mature ribbons and that Kif1aa is likely required for fusion events associated with ribbon maturation. Overall, the data provide a new and interesting story on ribbon synapse dynamics.

      Strengths:

      (1) The manuscript offers a comprehensive Introduction and Discussion sections that will inform generalists and specialists.

      (2) The use of Airyscan imaging in living samples to view and measure microtubule and ribbon dynamics in vivo represents a strength. With rigorous quantification and thoughtful analyses, the authors generate datasets often only obtained in cultured cells or more diminutive animal models (e.g., C. elegans).

      (3) The number of biological replicates and the statistical analyses are strong. The combination of pharmacology and genetic manipulations also represents strong rigor.

      (4) One of the most important strengths is that the manuscript and data spur on other questions - namely, do (or how do) ribbon bodies attach to Kinesin proteins? Also, and as noted in the Discussion, do hair cell activity and subsequent intracellular calcium rises facilitate ribbon transport/fusion?

      These are important strengths and as stated we are currently investigating what other kinesins and adaptors and adaptor’s transport ribbons. We have ongoing work examining how hair-cell activity impacts ribbon fusion and transport!

      Weaknesses:

      (1) Neither the data or the Discussion address a direct or indirect link between Kinesins and ribbon bodies. Showing Kif1aa protein in proximity to the ribbon bodies would add strength.

      This is a great point. Previous immunohistochemistry work in mice demonstrated that ribbons and Kif1a colocalize in mouse hair cells (Michanski et al, 2019). Unfortunately, the antibody used in study work did not work in zebrafish. To further investigate this interaction, we also attempted to create a transgenic line expressing a fluorescently tagged Kif1aa to directly visualize its association with ribbons in vivo. At present, we were unable to detect transient expression of Kif1aa-GFP or establish a transgenic line using this approach. While we will continue to work towards understanding whether Kif1aa and ribbons colocalize in live hair cells, currently this goal is beyond the scope of this paper. In our revision we discuss this caveat.

      Added to discussion:

      “In addition, it will be useful to visualize these kinesins by fluorescently tagging them in live hair cells to observe whether they associate with ribbons.”

      (2) Neither the data or Discussion address the functional consequences of loss of Kif1aa or ribbon transport. Presumably, both manipulations would reduce afferent excitation.

      Excellent point. Please see the response above to Reviewer #1 public response weaknesses.

      (3) It is unknown whether the drug treatments or genetic manipulations are specific to hair cells, so we can't know for certain whether any phenotypic defects are secondary.

      This is correct and a caveat of our Kif1aa and drug experiments. In our recently published work, we confirmed that Kif1aa is expressed in hair cells and neurons, while kif1ab is present just is neurons. Therefore, it is likely that the ribbon formation defects in kif1aa mutants are restricted to hair cells. We added this expression information to our results:

      “ScRNA-seq in zebrafish has demonstrated widespread co-expression of kif1ab and kif1aa mRNA in the nervous system. Additionally, both scRNA-seq and fluorescent in situ hybridization have revealed that pLL hair cells exclusively express kif1aa mRNA (David et al., 2024; Lush et al., 2019; Sur et al., 2023).”

      Non-hair cell effects are a real concern in our pharmacology experiments. To mitigate this in our pharmacological experiments, we have performed drug treatments at 3 different timescales: long-term (overnight), short-term (4 hr) and fast (30 min) treatments. The fast experiments were done after 30 min nocodazole drug treatment, and after this treatment we observed reduced directional motion and fusions. This fast drug treatment should not incur any long-term changes or developmental defects as hair-cell development occurs over 12-16 hrs. However, we acknowledge that drug treatments could have secondary phenotypic effects or effects that are not hair-cell specific. In our revision, we discuss these issues.

      Added to discussion:

      “Another important consideration is the potential off-target effects of nocodazole. Even at non-cytotoxic doses, nocodazole toxicity may impact ribbons and synapses independently of its effects on microtubules. While this is less of a concern in the short- and medium-term experiments (30-70 min and 4 hr), long-term treatments (16 hrs) could introduce confounding effects. Additionally, nocodazole treatment is not hair cell-specific and could disrupt microtubule organization within afferent terminals as well. Thus, the reduction in ribbon-synapse formation following prolonged nocodazole treatment may result from microtubule disruption in hair cells, afferent terminals, or a combination of the two.”

      Reviewer #3 (Public Review):

      Summary:

      The manuscript uses live imaging to study the role of microtubules in the movement of ribeye aggregates in neuromast hair cells in zebrafish. The main findings are that

      (1) Ribeye aggregates, assumed to be ribbon precursors, move in a directed motion toward the active zone;

      (2) Disruption of microtubules and kif1aa increases the number of ribeye aggregates and decreases the number of mature synapses.

      The evidence for point 2 is compelling, while the evidence for point 1 is less convincing. In particular, the directed motion conclusion is dependent upon fitting of mean squared displacement that can be prone to error and variance to do stochasticity, which is not accounted for in the analysis. Only a small subset of the aggregates meet this criteria and one wonders whether the focus on this subset misses the bigger picture of what is happening with the majority of spots.

      Strengths:

      (1) The effects of Kif1aa removal and nocodozole on ribbon precursor number and size are convincing and novel.

      (2) The live imaging of Ribeye aggregate dynamics provides interesting insight into ribbon formation. The movies showing the fusion of ribeye spots are convincing and the demonstrated effects of nocodozole and kif1aa removal on the frequency of these events is novel.

      (3) The effect of nocodozole and kif1aa removal on precursor fusion is novel and interesting.

      (4) The quality of the data is extremely high and the results are interesting.

      Weaknesses:

      (1) To image ribeye aggregates, the investigators overexpressed Ribeye-a TAGRFP under the control of a MyoVI promoter. While it is understandable why they chose to do the experiments this way, expression is not under the same transcriptional regulation as the native protein, and some caution is warranted in drawing some conclusions. For example, the reduction in the number of puncta with maturity may partially reflect the regulation of the MyoVI promoter with hair cell maturity. Similarly, it is unknown whether overexpression has the potential to saturate binding sites (for example motors), which could influence mobility.

      We agree that overexpression of transgenes under using a non-endogenous promoter in transgenic lines is an important consideration. Ideally, we would do these experiments with endogenously expressed fluorescent proteins under a native promoter. However, this was not technically possible for us. The decrease in precursors is likely not due to regulation by the myo6a promoter. Although the myo6a promoter comes on early in hair cell development, the promoter only gets stronger as the hair cells mature. This would lead to a continued increase rather than a decrease in puncta numbers with development.

      Protein tags such as tagRFP always have the caveat of impacting protein function. This is in partly why we complemented our live imaging with analyses in fixed tissue without transgenes (kif1aa mutants and nocodazole/taxol treatments).

      In our revision, we did perform an immunolabel on myo6b:riba-tagRFP transgenic fish and found that Riba-tagRFP expression did not impact ribbon synapse numbers or ribbon size. This analysis argues that the transgene is expressed at a level that does not impact ribbon synapses. This data is summarized in Figure 1-S1.

      Added to the results:

      “Although this latter transgene expresses Riba-TagRFP under a non-endogenous promoter, neither the tag nor the promoter ultimately impacts cell numbers, synapse counts, or ribbon size (Figure 1-S1A-E).”

      Added to methods:

      Tg(myo6b:ctbp2a-TagRFP)<sup>idc11Tg</sup> reliably labels mature ribbons, similar to a pan-CTBP immunolabel at 5 dpf (Figure 1-S1B). This transgenic line does not alter the number of hair cells or complete synapses per hair cell (Figure 1-S1A-D). In addition, myo6b:ctbp2a-TagRFP does not alter the size of ribbons (Figure 1-S1E).”

      (2) The examples of punctae colocalizing with microtubules look clear (Figures 1 F-G), but the presentation is anecdotal. It would be better and more informative, if quantified.

      We did attempt a co-localization analysis between microtubules and ribbons but did not move forward with it due to several issues:

      (1) Hair cells have an extremely crowded environment, especially since the nucleus occupies the majority of the cell. All proteins are pushed together in the small space surrounding the nucleus and ultimately, we found that co-localization analyses were not meaningful because the distances were too small.

      (2) We also attempted to segment microtubules in these images and quantify how many ribbons were associated with microtubules, but 3D microtubule segmentation was not accurate in hair cells due to highly varying filament intensities, filament dynamics and the presence of diffuse cytoplasmic tubulin signal.

      Because of these challenges we concluded the best evidence of ribbon-microtubule association is through visualization of ribbons and their association with microtubules over time (in our timelapses). We see that ribbons localize to microtubules in all our timelapses, including the examples shown (Movies S2-S10). The only instance of ribbon dissociation it when ribbons switch from one filament to another. We did not observe free-floating ribbons in our study.

      (3) It appears that any directed transport may be rare. Simply having an alpha >1 is not sufficient to declare movement to be directed (motor-driven transport typically has an alpha approaching 2). Due to the randomness of a random walk and errors in fits in imperfect data will yield some spread in movement driven by Brownian motion. Many of the tracks in Figure 3H look as though they might be reasonably fit by a straight line (i.e. alpha = 1).

      (4) The "directed motion" shown here does not really resemble motor-driven transport observed in other systems (axonal transport, for example) even in the subset that has been picked out as examples here. While the role of microtubules and kif1aa in synapse maturation is strong, it seems likely that this role may be something non-canonical (which would be interesting).

      Yes, it is true, that directed transport of ribbon precursors is relatively rare. Only a small subset of the ribbon precursors moves directionally (α > 1, 20 %) or have a displacement distance > 1 µm (36 %) during the time windows we are imaging. The majority of the ribbons are stationary. To emphasize this result we have added bar graphs to Figure 3I,K to illustrate this result and state the numbers behind this result more clearly.

      “Upon quantification, 20.2 % of ribbon tracks show α > 1, indicative of directional motion, but the majority of ribbon tracks (79.8 %) show α < 1, indicating confinement on microtubules (Figure 3I, n = 10 neuromasts, 40 hair cells, and 203 tracks).

      To provide a more comprehensive analysis of precursor movement, we also examined displacement distance (Figure 3J). Here, as an additional measure of directed motion, we calculated the percent of tracks with a cumulative displacement > 1 µm. We found 35.6 % of tracks had a displacement > 1 µm (Figure 3K; n = 10 neuromasts, 40 hair cells, and 203 tracks).”

      We cannot say for certain what is happening with the stationary ribbons, but our hypothesis is that these ribbons eventually exhibit directed motion sufficient to reach the active zone. This idea is supported by the fact that we see ribbons that are stationary begin movement, and ribbons that are moving come to a stop during the acquisition of our timelapses (Movies S4 and S5). It is possible that ribbons that are stationary may not have enough motors attached, or there may be a ‘seeding’ phase where Ribeye aggregates are condensing on the ribbon.

      We also reexamined our MSD a values as the a values we observed in hair cells were lower than those seen canonical motor-driven transport (where a approaches 2). One reason for this difference may arise from the dynamic microtubule network in developing hair cells, which could affect directional ribbon movement. In our revision we plotted the distribution of a values which confirmed that in control hair cells, the majority of the a values we see are typically less than 2 (Figure 7-S1A). Interestingly we also compared the distribution a values between control and taxol-treated hair cells, where the microtubule network is more stable, and found that the distribution shifted towards higher a values (Figure 7-S1A). We also plotted only ‘directional’ tracks (with a > 1) and observed significantly higher a values in taxol-treated hair cells (Figure 7-S1B). This is an interesting result which indicates that although the proportion of directional tracks (with a > 1) is not significantly different between control and taxol-treated hair cells (which could be limited by the number of motor/adapter proteins), the ribbons that move directionally do so with greater velocities when the microtubules are more stable. This supports our idea that the stability of the microtubule network could be why ribbon movement does not resemble canonical motor transport. This analysis is presented as a new figure (Figure 7-S1A-B) and is referred to in the text in the results and the discussion.

      Results:

      “Interestingly, when we examined the distribution of α values, we observed that taxol treatment shifted the overall distribution towards higher α a values (Figure 7-S1A). In addition, when we plotted only tracks with directional motion (α > 1), we found significantly higher α values in hair cells treated with taxol compared to controls (Figure 7-S1B). This indicates that in taxol-treated hair cells, where the microtubule network is stabilized, ribbons with directional motion have higher velocities.”

      Discussion:

      “Our findings indicate that ribbons and precursors show directed motion indicative of motor-mediated transport (Figure 3 and 7). While a subset of ribbons moves directionally with α values > 1, canonical motor-driven transport in other systems, such as axonal transport, can achieve even higher α values approaching 2 (Bellotti et al., 2021; Corradi et al., 2020). We suggest that relatively lower α values arise from the highly dynamic nature of microtubules in hair cells. In axons, microtubules form stable, linear tracks that allow kinesins to transport cargo with high velocity. In contrast, the microtubule network in hair cells is highly dynamic, particularly near the cell base. Within a single time frame (50-100 s), we observe continuous movement and branching of these networks. This dynamic behavior adds complexity to ribbon motion, leading to frequent stalling, filament switching, and reversals in direction. As a result, ribbon transport appears less directional than the movement of traditional motor cargoes along stable axonal filaments, resulting in lower α values compared to canonical motor-mediated transport. Notably, treatment with taxol, which stabilizes microtubules, increased α values to levels closer to those observed in canonical motor-driven transport (Figure 7-S1). This finding supports the idea that the relatively lower α values in hair cells are a consequence of a more dynamic microtubule network. Overall, this dynamic network gives rise to a slower, non-canonical mode of transport.”

      (5) The effect of acute treatment with nocodozole on microtubules in movie 7 and Figure 6 is not obvious to me and it is clear that whatever effect it has on microtubules is incomplete.

      When using nocodazole, we worked to optimize the concentration of the drug to minimize cytotoxicity, while still being effective. While the more stable filaments at the cell apex remain largely intact after nocodazole treatment, there are almost no filaments at the hair cell base, which is different from the wild-type hair cells. In addition, nocodazole-treated hair cells have more cytoplasmic YFP-tubulin signal compared to wild type. We have clarified this in our results. To better illustrate the effect of nocodazole and taxol we have also added additional side-view images of hair cells expressing YFP-tubulin (Figure 4-S1F-G), that highlight cytoplasmic YFP-tubulin and long, stabilized microtubules after 3-4 hr treatment with nocodazole and taxol respectively. In these images we also point out microtubules at the apical region of hair cells that are very stable and do not completely destabilize with nocodazole treatment at concentrations that are tolerable to hair cells.

      “We verified the effectiveness of our in vivo pharmacological treatments using either 500 nM nocodazole or 25 µM taxol by imaging microtubule dynamics in pLL hair cells (myo6b:YFP-tubulin). After a 30-min pharmacological treatment, we used Airyscan confocal microscopy to acquire timelapses of YFP-tubulin (3 µm z-stacks, every 50-100 s for 30-70 min, Movie S8). Compared to controls, 500 nM nocodazole destabilized microtubules (presence of depolymerized YFP-tubulin in the cytosol, see arrows in Figure 4-S1F-G) and 25 µM taxol dramatically stabilized microtubules (indicated by long, rigid microtubules, see arrowheads in Figure 4-S1F,H) in pLL hair cells. We did still observe a subset of apical microtubules after nocodazole treatment, indicating that this population is particularly stable (see asterisks in Figure 4-S1F-H).”

      To further address concerns about verifying the efficacy of nocodazole and taxol treatment on microtubules, we added a quantification of our immunostaining data comparing the mean acetylated-a-tubulin intensities between control, nocodazole and taxol-treated hair cells. Our results show that nocodazole treatment reduces the mean acetylated-a-tubulin intensity in hair cells. This is included as a new figure (Figure 4-S1D-E) and this result is referred to in the text. To better illustrate the effect of nocodazole and taxol we have also added additional side-view images of hair cells after overnight treatment with nocodazole and taxol (Figure 4-S1A-C).

      “After a 16-hr treatment with 250 nM nocodazole we observed a decrease in acetylated-a-tubulin label (qualitative examples: Figure 4A,C, Figure 4-S1A-B). Quantification revealed significantly less mean acetylated-a-tubulin label in hair cells after nocodazole treatment (Figure 4-S1D). Less acetylated-a-tubulin label indicates that our nocodazole treatment successfully destabilized microtubules.”

      “Qualitatively more acetylated-a-tubulin label was observed after treatment, indicating that our taxol treatment successfully stabilized microtubules (qualitative examples: Figure 4-S1A,C). Quantification revealed an overall increase in mean acetylated-a-tubulin label in hair cells after taxol treatment, but this increase did not reach significance (Figure 4-S1E).”

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      (1) The manuscript is fairly dense. For instance, some information is repeated (page 3 ribbon synapses form along a condensed timeline in zebrafish hair cells: 12-18 hrs, and on .page 5. These hair cells form 3-4 ribbon synapses in just 12-18 hrs). Perhaps, the authors could condense some of the ideas? The introduction could be shortened.

      We have eliminated this repeated text in our revision. We have shortened the introduction 1275 to 1038 words (with references)

      (2) The mechanosensory structure on page 5 is not defined for readers outside the field.

      Great point, we have added addition information to define this structure in the results:

      “We staged hair cells based on the development of the apical, mechanosensory hair bundle. The hair bundle is composed of actin-based stereocilia and a tubulin-based kinocilium. We used the height of the kinocilium (see schematic in Figure 1B), the tallest part of the hair bundle, to estimate the developmental stage of hair cells as described previously…”

      (3) Figure 1E is quite interesting but I'd rather show Figure S1 B/C as they provide statistics. In addition, the authors define 4 stages : early, intermediate, late, and mature for counting but provide only 3 panels for representative examples by mixing late/mature.

      We were torn about which ribbon quantification graph to show. Ultimately, we decided to keep the summary data in Figure 1E. This is primarily because the supplementary Figure will be adjacent to the main Figure in the Elife format, and the statistics will be easy to find and view.

      Figure 1 now provides a representative image for both late and mature hair cells.

      (4.) The ribbon that jumps from one microtubule to another one is eye-catching. Can the authors provide any statistics on this (e.g. percentage)?

      Good point. In our revision, we have added quantification for these events. We observe 2.8 switching events per neuromast during our fast timelapses. This information is now in the text and is also shown in a graph in Figure 3-S1D.

      “Third, we often observed that precursors switched association between neighboring microtubules (2.8 switching events per neuromast, n= 10 neuromasts; Figure 3-S1C-D, Movie S7).”

      (5) With regard to acetyl-a-tub immunocytochemistry, I would suggest obtaining a profile of the fluorescence intensity on a horizontal plane (at the apical part and at the base).

      (6) Same issue with microtubule destruction by nocodazole. Can the authors provide fluorescence intensity measurements to convince readers of microtubule disruption for long and short-term application.

      Regarding quantification of microtubule disruption using nocodazole and taxol. We did attempt to create profiles of the acetylated tubulin or YFP-tubulin label along horizontal planes at the apex and base, but the amount variability among cells and the angle of the cell in the images made this type of display and quantification challenging. In our revision we as stated above in our response to Reviewer #1’s public comment, we have added representative side-view images to show the disruptions to microtubules more clearly after short and long-term drug experiments (Figure 4-S1A-C, F-H). In addition, we quantified the reduction in acetylated tubulin label after overnight treatment with nocodazole and found the signal was significantly reduced (Figure 3-S1D-E). Unfortunately, we were unable to do a similar quantification due to the variability in YFP-tubulin intensity due to variations in mounting. The following text has been added to the results:

      “Quantification revealed significantly less mean acetylated-a-tubulin label in hair cells after nocodazole treatment (Figure 4-S1D).”

      “Quantification revealed an overall increase in mean acetylated-a-tubulin label in hair cells after taxol treatment, but this increase did not reach significance (Figure 4-S1A,C,E).”

      (7) It is a bit difficult to understand that the long-term (overnight) microtubule destabilization leads to a reduction in the number of synapses (Figure 4F) whereas short-term (30 min) microtubule destabilization leads to the opposite phenotype with an increased number of ribbons (Figure 6G). Are these ribbons still synaptic in short-term experiments? What is the size of the ribbons in the short-term experiments? Alternatively, could the reduction in synapse number upon long-term application of nocodazole be a side-effect of the toxicity within the hair cell?

      Agreed-this is a bit confusing. In our revision, we have changed our analyses, so the comparisons are more similar between the short- and long-term experiments–we examined the number of ribbons and precursor per cells (apical and basal) in both experiments (Changed the panel in Figure 4G, Figure 4-S2G and Figure 5G). In our live experiments we cannot be sure that ribbons are synaptic as we do not have a postsynaptic co-label. Also, we are unable to reliably quantify ribbon and precursor size in our live images due to variability in mounting. We have changed the text to clarify as follows:

      Results:

      “In each developing cell, we quantified the total number of Riba-TagRFP puncta (apical and basal) before and after each treatment. In our control samples we observed on average no change in the number of Riba-TagRFP puncta per cell (Figure 6G). Interestingly, we observed that nocodazole treatment led to a significant increase in the total number of Riba-TagRFP puncta after 3-4 hrs (Figure 6G). This result is similar to our overnight nocodazole experiments in fixed samples, where we also observed an increase in the number of ribbons and precursors per hair cell. In contrast to our 3-4 hr nocodazole treatment, similar to controls, taxol treatment did not alter the total number of Riba-TagRFP puncta over 3-4 hrs (Figure 6G). Overall, our overnight and 3-4 hr pharmacology experiments demonstrate that microtubule destabilization has a more significant impact on ribbon numbers compared to microtubule stabilization.”

      Discussion:

      “Ribbons and microtubules may interact during development to promote fusion, to form larger ribbons. Disrupting microtubules could interfere with this process, preventing ribbon maturation. Consistent with this, short-term (3-4 hr) and long-term (overnight) nocodazole increased ribbon and precursor numbers (Figure 6AG; Figure 4G), suggesting reduced fusion. Long-term treatment (overnight) resulted in a shift toward smaller ribbons (Figure 4H-I), and ultimately fewer complete synapses (Figure 4F).”

      Nocodazole toxicity: in response to Reviewer # 2’s public comment we have added the following text in our discussion:

      Discussion:

      “Another important consideration is the potential off-target effects of nocodazole. Even at non-cytotoxic doses, nocodazole toxicity may impact ribbons and synapses independently of its effects on microtubules. While this is less of a concern in the short- and medium-term experiments (30 min to 4 hr), long-term treatments (16 hrs) could introduce confounding effects. Additionally, nocodazole treatment is not hair cell-specific and could disrupt microtubule organization within afferent terminals as well. Thus, the reduction in ribbon-synapse formation following prolonged nocodazole treatment may result from microtubule disruption in hair cells, afferent terminals, or a combination of the two.”

      (8) Does ribbon motion depend on size or location?

      It is challenging to reliability quantify the actual area of precursors in our live samples, as there is variability in mounting and precursors are quite small. But we did examine the location of ribbon precursors (using tracks > 1 µm as these tracks can easily be linked to cell location in Imaris) with motion in the cell. We found evidence of ribbons with tracks > 1 µm throughout the cell, both above and below the nucleus. This is now plotted in Figure 3M. We have also added the following test to the results:

      “In addition, we examined the location of precursors within the cell that exhibited displacements > 1 µm. We found that 38.9 % of these tracks were located above the nucleus, while 61.1 % were located below the nucleus (Figure 3M).”

      Although this is not an area or size measurement, this result suggests that both smaller precursors that are more apical, and larger precursors/ribbons that are more basal all show motion.

      (9) The fusion event needs to be analyzed in further detail: when one ribbon precursor fuses with another one, is there an increase in size or intensity (this should follow the law of mass conservation)? This is important to support the abstract sentence "ribbon precursors can fuse together on microtubules to form larger ribbons".

      As mentioned above it is challenging accurately estimate the absolute size or intensity of ribbon precursors in our live preparation. But we did examine whether there is a relative increase in area after ribbon fuse. We have plotted the change in area (within the same samples) for the two fusion events in shown in Figure 8-S1A-B. In these examples, the area of the puncta after fusion is larger than either of the two precursors that fuse. Although the areas are not additive, these plots do provide some evidence that fusion does act to form larger ribbons. To accompany these plots, we have added the following text to the results:

      “Although we could not accurately measure the areas of precursors before and after fusion, we observed that the relative area resulting from the fusion of two smaller precursors was greater than that of either precursor alone. This increase in area suggests that precursor fusion may serve as a mechanism for generating larger ribbons (see examples: Figure 8-S1A-B).”

      Because we were unable to provide more accurate evidence of precursor fusion resulting in larger ribbons, we have removed this statement from our abstract and lessened our claims elsewhere in the manuscript.

      (10) The title in Figure 8 is a bit confusing. If fusion events reflect ribbon precursors fusion, it is obvious it depends on ribbon precursors. I'd like to replace this title with something like "microtubules and kif1aa are required for fusion events"

      We have changed the figure title as suggested, good idea.

      Reviewer #2 (Recommendations For The Authors):

      (1) Figure 1C. The purple/magenta colors are hard to distinguish.

      We have made the magenta color much lighter in the Figure 1C to make it easier to distinguish purple and magenta.

      (2) There are places where some words are unnecessarily hyphenated. Examples: live-imaging and hair-cell in the abstract, time-course in the results.

      In our revision, we have done our best to remove unnecessary hyphens, including the ones pointed out here.

      (3) Figure 4H and elsewhere - what is "area of Ribeye puncta?" Related, I think, in the Discussion the authors refer to "ribbon volume" on line 484. But they never measured ribbon volume so this needs to be clarified.

      We have done best to clarify what is meant by area of Ribeye puncta in the results and the methods:

      Results:

      “We also observed that the average of individual Ribeyeb puncta (from 2D max-projected images) was significantly reduced compared to controls (Figure 4H). Further, the relative frequency of individual Ribeyeb puncta with smaller areas was higher in nocodazole treated hair cells compared to controls (Figure 4I).”

      Methods:

      “To quantify the area of each ribbon and precursor, images were processed in a FIJI ‘IJMacro_AIRYSCAN_simple3dSeg_ribbons only.ijm’ as previously described (Wong et al., 2019). Here each Airyscan z-stack was max-projected. A threshold was applied to each image, followed by segmentation to delineate individual Ribeyeb/CTBP puncta. The watershed function was used to separate adjacent puncta. A list of 2D objects of individual ROIs (minimum size filter of 0.002 μm2) was created to measure the 2D areas of each Ribeyeb/CTBP puncta.”

      We did refer to ribbon volume once in the discussion, but volume is not reflected in our analyses, so we have removed this mention of volume.

      (4) More validation data showing gene/protein removal for the crispants would be helpful.

      Great suggestion. As this is a relatively new method, we have created a figure that outlines how we genotype each individual crispant animal analyzed in our study Figure 6-S1. In the methods we have also added the following information:

      “fPCR fragments were run on a genetic analyzer (Applied Biosystems, 3500XL) using LIZ500 (Applied Biosystems, 4322682) as a dye standard. Analysis of this fPCR revealed an average peak height of 4740 a.u. in wild type, and an average peak height of 126 a.u. in kif1aa F0 crispants (Figure 6-S1). Any kif1aa F0 crispant without robust genomic cutting or a peak height > 500 a.u. was not included in our analyses.”

      Reviewer #3 (Recommendations For The Authors):

      Lines 208-209--should refer to the movie in the text.

      Movie S1 is now referenced here.

      It would be helpful if the authors could analyze and quantify the effect of nocodozole and taxol on microtubules (movie 7).

      See responses above to Reviewer #1’s similar request.

      Figure 7 caption says "500 mM" nocodozole.

      Thank you, we have changed the caption to 500 nM.

      One problem with the MSD analysis is that it is dependent upon fits of individual tracks that lead to inaccuracies in assigning diffusive, restricted, and directed motion. The authors might be able to get around these problems by looking at the ensemble averages of all the tracks and seeing how they change with the various treatments. Even if the effect is on a subset of ribeye spots, it would be reassuring to see significant effects that did not rely upon fitting.

      We are hesitant to average the MSD tracks as not all tracks have the same number of time steps (ribbon moving in and out of the z-stack during the timelapse). This makes it challenging for us to look at the ensembles of all averages accurately, especially for the duration of the timelapse. This is the main reason why added another analysis, displacements > 1µm as another readout of directional motion, a measure that does not rely upon fitting.

      The abstract states that directed movement is toward the synapse. The only real evidence for this is a statement in the results: "Of the tracks that showed directional motion, while the majority move to the cell base, we found that 21.2 % of ribbon tracks moved apically." A clearer demonstration of this would be to do the analysis of Figure 2G for the ribeye aggregates.

      If was not possible to do the same analysis to ribbon tracks that we did for the EB3-GFP analysis in Figure 2. In Figure 2 we did a 2D tracking analysis and measured the relative angles in 2D. In contrast, the ribbon tracking was done in 3D in Imaris not possible to get angles in the same way. Further the MSD analysis was outside of Imaris, making it extremely difficult to link ribbon trajectories to the 3D cellular landscape in Imaris. Instead, we examined the direction of the 3D vectors in Imaris with tracks > 1µm and determined the direction of the motion (apical, basal or undetermined). For clarity, this data is now included as a bar graph in Figure 3L. In our results, we have clarified the results of this analysis:

      “To provide a more comprehensive analysis of precursor movement, we also examined displacement distance (Figure 3J). Here, as an additional measure of directed motion, we calculated the percent of tracks with a cumulative displacement > 1 µm. We found 35.6 % of tracks had a displacement > 1 µm (Figure 3K; n = 10 neuromasts, 40 hair cells and 203 tracks). Of the tracks with displacement > 1 µm, the majority of ribbon tracks (45.8 %) moved to the cell base, but we also found a subset of ribbon tracks (20.8 %) that moved apically (33.4 % moved in an undetermined direction) (Figure 3L).”

      Some more detail about the F0 crispants should be provided. In particular, what degree of cutting was observed and what was the criteria for robust cutting?

      See our response to Reviewer 2 and the newly created Figure 6-S1.

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      Reply to the reviewers

      1. General Statements [optional]

      *We would like to thank all the reviewers for their positive comments and valuable feedback. In addition, we would like to address reviewer 1 query on novelty, which was not questioned by the other 2 reviewers. Our study uncovered two main aspects of hypoxia biology: first we addressed the role of NF-kappaB contribution towards the transcriptome changes in hypoxia, and second, this revealed a previously unknown aspect, that NF-kappaB is required for gene repression in hypoxia. While we know a lot about gene induction in hypoxia, much less is known about repression of genes. In times of energy preservation, gene repression is as important as gene induction. *

      .

      2. Point-by-point description of the revisions

      This section is mandatory. *Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. *

      • *

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

      The work from Shakir et al uses different cell line models to investigate the role of NF-kB in the transcriptional adaptation of cells to hypoxia, which is relevant. In addition, the manuscript contains a large amount of data that could be of interest and even useful for researchers in the field of hypoxia and NF-kB. However, in my opinion, there are several concerns that should be revised and additional experiments that could be included to strengthen the relevance of the work.

      We thank this reviewer for their positive comments.

      Specific issues: In Figure 1A, the authors examine which of the genes induced by hypoxia require NF-kB by RNA sequencing analysis of cells knocked down for specific NF-kB subunits and exposed to hypoxia for 24 hours. The knockdown is about 40-60% at the RNA level, but it would be helpful to show the effect of knockdown at the protein level.

      We agree with this and have added Western blot data (Sup. Figure S1F), which shows the effects of the siRNA are much more pronounced at the protein level.

      All the data regarding genes induced by hypoxia in control or NF-kB siRNA-treated cells are somewhat confusing. If I understand correctly, when the data from the three different siRNAs are crossed, only 1070 genes are upregulated and 295 are downregulated in an NF-kB-independent manner. If this is the case, I think it would be easier to use this information in Figure 2 to define the hypoxia-induced genes that are NF-kB-dependent by simply considering those induced in the control that are not in the NF-kB-independent subset (rather than repeating the integration of the data without additional explanation). If the authors do this simple analysis, are the resulting genes the same or similar? In any case, the way these numbers are obtained should be shown more clearly (i.e., a new Venn diagram showing genes up- or down-regulated in the siRNA control that are not up- or down-regulated in any of the siRNA-NF-kB treatments).

      Figure 1 shows the effects on gene expression of hypoxia in control and NF-____k____B ____subunit____-depleted cells compared to normoxia control cells. Figures 1F/1G compares genes up/downregulated in hypoxia when RelA, RelB, and cRel are depleted, compared to normoxia control. Figure 1 does not display N____F-____k____B____-dependent/independent hypoxia-responsive genes____, but rather the overall effect of siRNA control and siNF-____k____B treatments in hypoxia, compared to siRNA control in normoxia. Figure 2 then defines NF-____k____B-dependent ____and independent hypoxia-responsive genes. We actually define these exactly as the reviewer suggested and agree that we should show the way these numbers are obtained more clearly. We have added the suggested Venn diagrams (Sup. Figure S2) and added extra information to the methods section (page 5 of revised manuscript). We felt it was important to show all the data upfront in Figure 1 and then integrate and focus on NF-____k____B-dependent ____hypoxia-induced genes in Figure 2.

      Figure 2H shows that approximately 80% of the NF-kB-dependent genes up- or down-regulated in hypoxia were identified as RelA targets, which is statistically significant compared to RelB or cRel targets. However, what is the proportion of genes identified as RelA targets in the subset of NF-kB-independent hypoxia-induced genes? And in a randomly selected set of 500-600 genes? In my opinion, this statistical analysis should be included to demonstrate a relationship between NF-kB recruitment and hypoxia-induced upregulation (expected) and downregulation (unexpected). In this context, it is surprising that HIF consensus sites are preferentially detected in the genes that are supposed to be NF-kB dependent instead of RelA consensus.

      We thank the reviewer for this question, which is really helpful. The way we have displayed the stars on the graph for Figure 2H was slightly misleading we realize now. As such, we have amended the graph. RelA, RelB, and cRel bound genes (from the ChIP atlas) are all significantly enriched within our N____F-____k____B-dependent hypoxia-responsive genes, there is no statistical testing between RelA bound vs RelB bound or cRel bound. We have also performed this analysis on the NF-____k____B____-independent hypoxia-responsive genes ____and see the same trend (Sup. Figure S5B). This indicates that the enrichment of Rel binding sites from the ChIP atlas is not specific to NF-____k____B____-dependent hypoxia-responsive genes____. We have moved Figure 2H to (Sup. Figure S5A) and amended our description of the finding. This showcases how DNA binding does not necessarily mean functionality. We have amended our description of this result and limitation of the study.

      Figure 3 is just a confirmation by qPCR of the data obtained in the RNA-seq analysis, which in my opinion should be included as supplementary information. Moreover, both the effects of hypoxia and reversion by RelB siRNA are modest in several of the genes tested. The same is true for Figures 4 and 5 with very modest and variable results across cell types and genes.

      We appreciate this comment; we would like to keep this as a main figure for full transparency and show validation of our RNA-sequencing results.

      Figure 6 shows the effect of NF-kB knockdown on the induction of ROS in response to hypoxia. In the images provided, the effect of hypoxia is minimal in control cells, with the only clear differences shown in RelA-depleted cells.

      The quantification of the IF data (Figure 6B) shows ROS induction in hypoxia which is reduced in Rel-depleted cells, with RelA depletion having the strongest effect. ROS generation in hypoxia, although counterintuitive, is well documented and used for important signalling events. We believe our data supports the previously reported levels of ROS induction (reviewed in {Alva, 2024}) in hypoxia and importantly, that NF-____k____B depletion can at least partially____ reverse this.

      In 6B it is not clear what the three asterisks in the normoxia control represent (compared to the hypoxia siRNA control?). This should be clarified in the figure legend or text.

      We apologize for the lack of clarity we have now added this information to the figure legend.

      In the Western blot of 6C, there are no differences in the levels of SOD1 after RelA depletion. Again, there is no reason not to include the NF-kB subunits in the Western blot analysis.

      We have added the Western blot analysis to this figure. We were trying to simplify it. Although depletion of RelA does not rescue the hypoxia-induced repression of SOD1, depletion of RelB does. Furthermore, cRel although not statistically significant, has a trend for the rescue of this effect, see Figure 6C-D.

      Finally, regarding Figure 7, the authors mention that "we confirmed that hypoxia led to a reduction in several proteins represented in this panel (of proteins involved in oxidative phosphorylation), such as UQCRC2 and IDH1 (Figure 7A-B)". The authors cannot say this because it is not seen in the Western blot in 7A or in the quantification shown in 7B. In my personal opinion, stating something that is not even suggested in the experiments is very negative for the credibility of the whole message.

      We really do not agree with this comment. We do see reductions in the levels of the proteins we mentioned. We have made the figure less complex given that some proteins are very abundant while others are not. We hope the changes are now clear and apparent. We have changed the quantification normalisation to reflect this as well and modified our description of the results, see Figure 7 and Sup. Figure S18.

      In conclusion, this paper contains a large amount of relevant information, but i) non-essential data should be moved to Supplementary, ii) protein levels of relevant players need to be shown in addition to RNA, iii) minimal or undetectable differences need to be considered as no-differences, and iv) a model showing what is the interpretation of the data provided is needed to better understand the message of the paper. I mean, is it p65 or RelB binding to some of these genes leading to their activation or repression, or is it RelA or RelB inducing HIF1beta leading to NF-kB-dependent gene activation by hypoxia? If this were the case, experimental evidence that NF-kB regulates a subset of hypoxia genes through HIF1beta would make the story more understandable.

      We apologise but we do not know why the reviewer mentions HIF1beta. For gene induction, there is cooperation with the HIF system in some genes but not all. The most interesting and unexpected finding is that NF-kappaB is required for gene repression in hypoxia. We have added a new figure, investigating how HDAC inhibition could reverse the repression. A mechanism known to be employed by NF-kappaB when repressing genes. We have added all the blots for NF-kB, clarified the quantification and included other approaches including a CRISPR KO cell lines for both IKKs. We hope this is now clear.

      Reviewer #1 (Significance (Required)):

      The work presented here is interesting but does not provide a major advance over previous publications, the main message being that a subset of hypoxia-regulated genes are NF-kB dependent. However, there is no mechanistic explanation of how this regulation is achieved and several data that are not clearly connected. A more comprehensive analysis of the data and additional experimental validation would greatly enhance the significance of the work.

      We politely disagree with the reviewer. Our main finding is that NF-____k____B____ does play an important role in gene regulation in hypoxia but unexpectedly, this occurs mostly via gene repression. While there is vast knowledge on gene induction in hypoxia, gene repression, which typically does not occur directly via HIF, is virtually unknown. A previous study had identified Rest as a transcriptional repressor {PMID: 27531581} but this could only account for 20% of gene repression. Our findings reveal up to 60% of genes repressed in hypoxia require NF-____k____B____, hence this is a significant finding and a major advance over previous knowledge. Furthermore, we feel this paper is an excellent data resource for the field, as it is, to our knowledge, the first study characterising the extent to which NF-____k____B is required for hypoxia-induced gene changes, on a transcriptome-wide scale. Furthermore, we have validated this across multiple cell types and also used different approaches to investigate the role of NF-kB in the hypoxia transcriptional response. We are happy that the other reviewers agree with our novel findings.

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

      In this study, the authors have interrogated the role of NF-kappaB in the cellular transcriptional response to hypoxia. While HIF is considered the master regulator of the cellular response to hypoxia, it has long been known that mutliple transcription factors also play a role both independently of HIF and through the regulation of HIF-1alpha levels. Chief amongst these is NF-kappaB, a regulator of cell death and inflammation amongst other things. While NF-kappB has been known to be activated in hypoxia through altered PhD activity, the impact of this on global gene expression has remained unclear and this study addresses this important question. Of particular interest, genes downregulated in hypoxia appear to be repressed in a NF-kappaB-dependent manner. Overall, this nice study reveals an important role for NF-kappaB in the control of the global cellular transcriptional response to hypoxia.

      We thank this reviewer for their positive comments.

      Reviewer #2 (Significance (Required)):

      Some questions for the authors to consider with experiments or discussion: -One caveat of the current study which should be discussed is that while interesting and extensive, the analysis is restricted to cancer cell lines which have dysfunctional gene expression systems which may differ from "normal" cells. This should be discussed.

      We thank the reviewer for these comments. This is indeed an important aspect, which we now expand on in the discussion section. We also took advantage of RNA-seq datasets for HUVECs (a non-transformed cell lines) in response to hypoxia (Sup. Figure S15), TNF-alpha with and without RelA depletion (Sup. Figure S16). These data support our findings that in hypoxia NF-kB is important for transcriptional repression, with some contributions to gene induction, even in a non-transformed cell system.

      In the publicly available data sets analyzed, were the same hypoxic conditions used as in this study. This information should be included.

      We apologize if this was not clear, the hypoxia RNA-seq studies are the same oxygen level and time (1%, 24 hours), this is in the legend of Figure 4A and Sup. Figure S9 and in Sup. Table S2. We have added this information to the main text also.

      • What is known about NF-kappaB as a transcriptional repressor in other systems such as the control of cytokine or infection driven inflammation? This is briefly discussed but should be expanded. This is important as a key question in the study of hypoxia is what regulates gene repression.

      We have included this in the discussion and also analysed available data in HUVECs in response to cytokine stimulation with and without RelA depletion (Sup. Figure S16). This analysis revealed equal importance of RelA for activation and repression of genes upon TNF-alpha stimulation. Around 40% of genes require RelA for their induction or repression in response to TNF-a. In the discussion we have also included other references where NF-kappaB has been found to repress genes.

      NF-kappaB has previously been shown to regulate HIF-1alpha transcription. What are the effects of NF-kappaB subunit siRNAs on basal HIF-1alpha transcription? In figure 7, it appears that NF-kappaB subunit siRNA is without effect on hypoxia-induced HIF protein expression. Could this account for some of the effects of NF-kappaB depletion on the hypoxic gene signature? This point needs to be clarified in light of the data presented.

      We have included data for HIF-1α RNA levels in HeLa cells with/without NF-____k____B____ depletion followed by 24 hours of hypoxia (Sup. Figure S20) and we see a small reduction (~10-20%). The reviewer is correct, there was not much effect of NF-____k____B____ depletion on HIF-1α protein levels following 24 hours hypoxia in HeLa cells. Effects of NF-kappaB depletion can be found usually with lower times of hypoxia exposure or when more than one subunit is depleted at the same time. We have added this as a discussion point in the revised manuscript.

      NRF-2 is a key cellular sensor of oxidative stress in a similar way to HIF being a hypoxia sensor. The authors demonstrate using a dye that ROS are paradoxically increased in hypoxia (a more controversial finding than the authors present). It would be of interest to know if NFR-2 is induced in hypoxia as a marker of cellular oxidative stress. Similarly, it would be interesting to determine by metabolic analysis whether oxidative phosphorylation (O2 consumption) is decreased as the transcriptional signature would suggest (although the difficulty of performing metabolic analysis in hypoxia is acknowledged).

      To investigate if NRF2 is induced, we performed a western blot at 0, 1, and 24 hours 1% oxygen, but didn’t see any induction of NRF2 protein levels (____Sup. Figure S17A). We also overlapped our hypoxia upregulated genes with NRF2 target genes from {PMID:24647116 and PMID: 38643749} (Sup. Figure S17B) and found limited evidence of NRF2 target genes being induced. Based on these findings, it seems that NRF2 is not being induced in hypoxia, at least not at the hypoxia level/time point we have analysed. We also agree it would be ideal to measure oxygen consumption in hypoxia, but unfortunately, we do not have the technical ability to do this at present.

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

      Strengths This manuscript attempts to integrate multiple strands of data to determine the role of NFkB in hypoxia -induced gene expression. This analysis looks at multiple NFkB subunits in multiple cell lines to convincingly demonstrate that NFkB does indeed play a central role in the regulation of hypoxia-induced gene expression. This broad approach integrates new experimental data with findings from the published literature.

      A significant amount of work has been performed both experimentally and bioinformatically to test experimental hypotheses.

      We thank this reviewer for their positive comments.

      Limitations

      The main analysis in the paper involves comparing the impact of knocking down different NFkB family members in hypoxia and comparing transcriptional responses. I am surprised that the authors did not include the impact of knockdown of the NFkB family members in normoxia too. The absence of these control experiments allows us to understand the role of NFkB in hypoxia, but does not give us information as to how many of those impacts are specific/ induced in hypoxic conditions. i.e. many of the observed effects of NFkB knockdown could be due to basal suppression of NFkB target genes that happen to be hypoxia sensitive. This finding is obviously important, but it would be nice to know how many of those genes are only / preferentially regulated by NFkB in hypoxia. This would give a much deeper insight into the role of NFkB in hypoxia induced gene expression.

      We agree this would have been ideal. For financial reasons we limited our analysis to hypoxia samples. We have performed qPCR analysis depleting RelA, RelB and cRel under normal oxygen conditions in HeLa (Sup. Figure S8). We find that the majority of the validated genes in HeLa cells which require____ NF-____k____B for gene changes in hypoxia, are not regulated by N____F-____k____B under normal oxygen conditions____. We have also added this limitation into our discussion section.

      The broad experimental approach while a strength of the paper in many ways also has its limitations e.g. Motif analysis revealing e.g. HIF-1a binding site enrichment in RelA and RelB-dependent DEGs is correlative observation and does not prove HIF involvement in NFkB-dependent hypoxia induced gene activation. Comparing responses with responses seen in one cell type with responses that have been described in a database comprised of many studies in a variety of different cells also has some limitations. These points can be described more fully in the discussion

      We agree these are mere correlations and hence a limitation and we have not formerly tested the involvement of HIF. We have included this in the discussion as suggested. For HIF binding site correlation, we do also compare to HIF ChIP-seq in HeLa cells exposed to 1% oxygen, albeit at 8 hours and not 24 hours (Sup. Figure S4).

      For siRNA transfections, single oligonucleotide sequences were used for RelA, RelB and cRel. This increases the potential likelihood of 'off targets' compared to pooled oligos delivered at lower concentrations. This limitation should at least be mentioned.

      We agree and have now included this as a limitation in the discussion section. We have now also included analysis using wild type and 2 different IKK____________ double KO CRISPR cell lines generated in the following publication {PMID: 35029639}. Out of the 9 genes we identified as NF-____k____B-dependent hypoxia upregulated genes from HeLa cell RNA-seq and validated by qPCR, which are also hypoxia-responsive in HCT116 cells (Sup. Figure S11D), 6 displayed ____NF-____k____B dependence in HCT116 cells (Sup. Figure S14). We also provide new protein data in this cell system for oxidative phosphorylation markers, which show as with the siRNA depletion, rescue of repression of these proteins when NF-____k____B is inactivated.

      RNA-seq experiments are performed on n=2 data which means relatively low statistical power. How has the statistical analysis been performed on normalised counts (corresponding to 2 n- numbers) to yield statistical significance? I am not familiar with hypergeometric tests - please justify their use here.

      __*We use DESeq2 for differential expression analysis and filter for effect size (> -/+ 0.58 log2 fold change) and statistical significance (FDR I am not familiar with hypergeometric tests - please justify their use here.

      The hypergeometric test (equivalent to a one-sided Fisher's exact test) is routinely used to determine whether the observed overlap between two gene lists is statistically significant compared to what would be expected by chance. It is also the statistical test of choice for popular bioinformatics tools which perform over representation analysis (ORA) to see which gene sets/groups/pathways/ontologies are over-represented in a gene list, examples include Metascape, clusterProfiler, WebGestalt (used in this study), and gProfiler.

      P14 RelB is described as having the most widespread impact of hypoxia dependent gene changes across all cell systems tested. Could this be due to a more potent silencing of RelB and / or due to particularly high/ low expression of RelB in these cells in general?

      This is an excellent point, at the RNA level the RelB depletion is slightly more efficient (Sup. Figure S1), at the protein level, silencing is highly potent with all 3 siRNAs (Sup. Figure S1). We looked at the RNA levels of RelA, RelB and cRel in HeLa cells at basal conditions, and RelA shows the highest abundance compared to RelB and cRel, while RelB and cRel have similar expression levels (see below). However, RelB is very dynamic in response to hypoxia, something we have observed but have not published yet.

      P18 For western blot analysis best practise is to have 2 MW markers per blot presented

      We have and have added the second MW markers suggested.

      For quantification, I suggest avoiding performing statistical analysis on semi-quantitative data unless a dynamic range of detection (with standards) has been fully established.

      We agree this has many limitations, we will keep the quantification but moved into supplementary information.

      P19 There is clearly an effect of reciprocal silencing with the NFkB knockdown experiments ie. siRelA affects RelB levels in hypoxia and vice versa. The implications of this for data interpretation should be discussed.

      Indeed, it is well known that RelB and cRel are RelA targets. Less is known about RelA as it is not a known NF-____k____B____ target. We have added a discussion in the revised manuscript.

      P20 The literature can be better cited in relation RelB and hypoxia A brief search reveals a few papers that should be mentioned/ discussed. Oliver et al. 2009 Patel et al. 2017 Riedl et al. 2021

      We have looked into these suggestions. Oliver et al, refer to hypercapnia, not hypoxia and the other two only briefly mentioned RelB with no effects toward the goals of their studies. We have tried to incorporate what is currently known as much as possible.

      I suggest leaving out mention of IkBa sumoylation and supplementary figure 10. I'm not sure the data in the paper as a whole merits focus on this very specific point.

      We thank the reviewer for this suggestion and we have removed this aspect from the manuscript.

      There is a very strong reliance on mRNA and TPM data. Some additional protein data in support of key findings will enhance

      We have added additional protein level analysis where we could obtain antibodies, see Figures 6, 7 and Sup. Figures S17, S18, and S19 for our protein level analysis.

      A graphical abstract summarising key findings with exemplar genes highlighted will enhance.

      We have added a model to summarise our findings as suggested.

      Both HIF and NFKB are ancient evolutionarily conserved pathways. Can lessons be learned from evolutionary biology as to how NFkB regulation of hypoxia induced genes occured. Does the HIF pathway pre-date the NFkB pathway or vice versa. This approach could be valuable in supporting the findings from this study.

      We have investigated this. Unfortunately, there are very little available data on hypoxia gene expression in lower organisms. However, we have added a few sentences on the evolution of NF-____k____B____ and HIF.

      Minor comments P2 please briefly explain how 5 genes give rise to 7 proteins

      We have added this to the introduction as requested.

      P2 there seems to be some recency bias in the studies cited as being associated with NFkB activation in response to hypoxia. Mention of Koong et al (1994) and Taylor et al (1999) and other early papers in the field will enhance

      We have added these as suggested.

      P3 The role of PHD enzymes in the regulation of NFkB in hypoxia can be introduced and / or discussed

      We have added a reference to this aspect as suggested.

      P8 I suggest use of proportional Venn diagrams to demonstrate the patterns more clearly

      We have added these as suggested.

      P11 To what extent might NFkB and Rest co-operate/ co-regulate gene repression in hypoxia?

      This is a good question. We have overlapped our datasets with Rest-dependent hypoxia-regulated genes identified by Cavadas et al., (Figure below), and find that these appear to act independently of each other for the most part, with very few genes co-regulated by both.

      Reviewer #3 (Significance (Required)):

      Shakir et al. present a manuscript titled 'NFkB is a central regulator of hypoxia-induced gene expression'.

      The research group are experts in both NFkB and hypoxia signaling and are the ideal group to perform these studies.

      Hypoxia and inflammation are co-incident in many physiological and pathophysiological conditions, where the microenvironment affects disease severity and patient outcome. The cross talk between inflammatory and hypoxia signaling pathways is not fully described. Thus, this manuscript takes a novel approach to an established question and concludes clearly that NFkB is a central regulator of hypoxia-induced gene expression.

      We thank the reviewer for these positive comments.

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      Referee #1

      Evidence, reproducibility and clarity

      The work from Shakir et al uses different cell line models to investigate the role of NF-kB in the transcriptional adaptation of cells to hypoxia, which is relevant. In addition, the manuscript contains a large amount of data that could be of interest and even useful for researchers in the field of hypoxia and NF-kB. However, in my opinion, there are several concerns that should be revised and additional experiments that could be included to strengthen the relevance of the work.

      Specific issues:

      In Figure 1A, the authors examine which of the genes induced by hypoxia require NF-kB by RNA sequencing analysis of cells knocked down for specific NF-kB subunits and exposed to hypoxia for 24 hours. The knockdown is about 40-60% at the RNA level, but it would be helpful to show the effect of knockdown at the protein level. All the data regarding genes induced by hypoxia in control or NF-kB siRNA-treated cells are somewhat confusing. If I understand correctly, when the data from the three different siRNAs are crossed, only 1070 genes are upregulated and 295 are downregulated in an NF-kB-independent manner. If this is the case, I think it would be easier to use this information in Figure 2 to define the hypoxia-induced genes that are NF-kB-dependent by simply considering those induced in the control that are not in the NF-kB-independent subset (rather than repeating the integration of the data without additional explanation). If the authors do this simple analysis, are the resulting genes the same or similar? In any case, the way these numbers are obtained should be shown more clearly (i.e., a new Venn diagram showing genes up- or down-regulated in the siRNA control that are not up- or down-regulated in any of the siRNA-NF-kB treatments). Figure 2H shows that approximately 80% of the NF-kB-dependent genes up- or down-regulated in hypoxia were identified as RelA targets, which is statistically significant compared to RelB or cRel targets. However, what is the proportion of genes identified as RelA targets in the subset of NF-kB-independent hypoxia-induced genes? And in a randomly selected set of 500-600 genes? In my opinion, this statistical analysis should be included to demonstrate a relationship between NF-kB recruitment and hypoxia-induced upregulation (expected) and downregulation (unexpected). In this context, it is surprising that HIF consensus sites are preferentially detected in the genes that are supposed to be NF-kB dependent instead of RelA consensus. Figure 3 is just a confirmation by qPCR of the data obtained in the RNA-seq analysis, which in my opinion should be included as supplementary information. Moreover, both the effects of hypoxia and reversion by RelB siRNA are modest in several of the genes tested. The same is true for Figures 4 and 5 with very modest and variable results across cell types and genes. Figure 6 shows the effect of NF-kB knockdown on the induction of ROS in response to hypoxia. In the images provided, the effect of hypoxia is minimal in control cells, with the only clear differences shown in RelA-depleted cells. In 6B it is not clear what the three asterisks in the normoxia control represent (compared to the hypoxia siRNA control?). This should be clarified in the figure legend or text. In the Western blot of 6C, there are no differences in the levels of SOD1 after RelA depletion. Again, there is no reason not to include the NF-kB subunits in the Western blot analysis. Finally, regarding Figure 7, the authors mention that "we confirmed that hypoxia led to a reduction in several proteins represented in this panel (of proteins involved in oxidative phosphorylation), such as UQCRC2 and IDH1 (Figure 7A-B)". The authors cannot say this because it is not seen in the Western blot in 7A or in the quantification shown in 7B. In my personal opinion, stating something that is not even suggested in the experiments is very negative for the credibility of the whole message. In conclusion, this paper contains a large amount of relevant information, but i) non-essential data should be moved to Supplementary, ii) protein levels of relevant players need to be shown in addition to RNA, iii) minimal or undetectable differences need to be considered as no-differences, and iv) a model showing what is the interpretation of the data provided is needed to better understand the message of the paper. I mean, is it p65 or RelB binding to some of these genes leading to their activation or repression, or is it RelA or RelB inducing HIF1beta leading to NF-kB-dependent gene activation by hypoxia? If this were the case, experimental evidence that NF-kB regulates a subset of hypoxia genes through HIF1beta would make the story more understandable.

      Significance

      The work presented here is interesting but does not provide a major advance over previous publications, the main message being that a subset of hypoxia-regulated genes are NF-kB dependent. However, there is no mechanistic explanation of how this regulation is achieved and several data that are not clearly connected. A more comprehensive analysis of the data and additional experimental validation would greatly enhance the significance of the work.

    1. Reviewer #3 (Public review):

      Summary

      Tanaka and colleagues addressed the role of the C-C chemokine receptor 4 (CCR4) in early atherosclerotic plaque development using ApoE-deficient mice on a standard chow diet as a model. Because several CD4+ T cell subsets express CCR4, they examined whether CCR4-deficiency alters the immune response mediated by CD4+ T cells. By histological analysis of aortic lesions, they demonstrated that the absence of CCR4 promoted the development of early atherosclerosis, with heightened inflammation linked to increased macrophages and pro-inflammatory CD4+ T cells, along with reduced collagen content. Flow cytometry and mRNA expression analysis for identifying CD4+ T cell subsets showed that CCR4 deficiency promoted higher proliferation of pro-inflammatory effector CD4+ T cells in peripheral lymphoid tissues and accumulation of Th1 cells in the atherosclerotic lesions. Interestingly, the increased pro-inflammatory CD4+ T cell response occurred despite the expansion of T CD4+ Foxp3+ regulatory cells (Tregs), found in higher numbers in lymphoid tissues of CCR4-deficient mice, suggesting that CCR4 deficiency interfered with Treg's regulatory actions. The findings contrast with earlier studies in a murine model of advanced atherosclerosis, where CCR4 deficiency did not alter the development of the aortic lesions. The authors included a thoughtful discussion about hypothetical mechanisms explaining these contrasting results, including putative differences in the role played by the CCL17/CCL22-CCR4 axis along the stages of atherosclerosis development in this murine model.

      Major strengths

      • Demonstration of CCR4 deficiency's impact on early atherosclerosis. CCR4 deficiency effects on the early atherosclerosis development in the Apoe-/-mice model were demonstrated by a quantitative analysis of the lesion area, inflammatory cell content and the expression profile of several pro- and anti-inflammatory markers.<br /> • Analysis of the T CD4+ response in various lymphoid tissues (peripheral and para-aortic lymph nodes and spleen) and the atherosclerotic aorta during the early phase of atherosclerosis in the Apoe-/-mice model. This analysis, combining flow cytometry and mRNA expression, showed that CCR4 deficiency enhanced T CD4+ cell activation, favouring the amplification of the typical biased Th1-mediated inflammatory response observed in the lymphoid tissues of hypercholesterolemic mice.<br /> • Treg transference experiments. Transference of Treg from Apoe-/- or Ccr4-/- Apoe-/- mice to Apoe-/- mice under a standard chow diet was useful for addressing the relevance of CCR4 expression on Tregs for the atheroprotective effect of this regulatory T cell subset during early atherosclerosis.

      Major weaknesses

      • Methodological Limitations: The controls used in the flow cytometry analysis were suboptimal, as neither cell viability nor doublets were assessed. This may have introduced artifacts, particularly when measuring less-represented cell populations within complex samples, such as in assays evaluating Treg migration to the aorta in atherosclerotic mice.<br /> • Incomplete understanding of CCR4-Mediated Mechanisms: The mechanisms by which CCR4 regulates early inflammation and the development of atherosclerosis were not fully clarified.

      I have previously addressed the study limitations and their global impact in my earlier reviews.

    1. Reviewer #3 (Public review):

      Summary:

      In this study, Stein and colleagues use a clever masking/attentional blink paradigm using Kanisza stimuli, coupled with EEG decoding and the NMDA antagonist memantine, to isolate putative neural markers of feedforward, lateral, and feedback processing.

      In two elegant experiments, they show that memantine selective influences EEG decoding of only illusory Kanisza surfaces (but not contour continuation or raw contrast), only when unmasked, only when attention is available (not when "blinked"), and only when task-relevant.

      This neatly implicates NMDA receptors in the feedback mechanisms that are believed to be involved in inferring illusory Kanisza surfaces, and builds a difficult bridge between the large body of human perceptual experiments and pharmacological and neurophysiological work in animals.

      Strengths:

      Three key strengths of the paper are 1) its elegant and thorough experimental design, which includes internal replication of some key findings, and 2) the clear pattern of results across the full set of experiments, and 3) its clear writing and presentation of results.

      The paper effectively reports a 4-way interaction, with memantine only influencing decoding of surfaces (1) that are unmasked (2), with attention available (3) and task-relevant (4). Nevertheless, the results are very clear, with a clear separation between null effects on other conditions and quite a strong (and thus highly selective) effect on this one intersection of conditions. This makes the pattern of findings very convincing.

      Weaknesses:

      Overall this is an impressive and important paper. However, to my mind there are two minor weaknesses.

      First, despite its clear pattern of neural effects, there is no corresponding perceptual effect. Although the manipulation fits neatly within the conceptual framework, and there are many reasons for not finding such an effect (floor and ceiling effects, narrow perceptual tasks etc), this does leave open the possibility that the observation is entirely epiphenomenal, and that the mechanisms being recorded here are not actually causally involved in perception per se.

      Second, although it is clear that there is an effect on decoding in this particular condition, what that means is not entirely clear - particularly since performance improves, rather than decreases. It should be noted here that improvements in decoding performance do not necessarily need to map onto functional improvements, and we should all be careful to remain agnostic about what is driving classifier performance. Here too, the effect of memantine on decoding might be epiphenomenal - unrelated to the information carried in the neural population, but somehow changing the balance of how that is electrically aggregated on the surface of the skull. *Something* is changing, but that might be a neurochemical or electrical side-effect unrelated to actual processing (particularly since no corresponding behavioural impact is observed.)

      Comments on revisions:

      I think the authors responsed fairly to my comments. Even if they weren't really able to add new insight into why behaviour didn't show the same effects as decoding, they discuss this in the revised text.

    2. Author response:

      The following is the authors’ response to the original reviews

      Reviewer #1:

      (1) I miss some treatment of the lack of behavioural correlate. What does it mean that metamine benefits EEG classification accuracy without improving performance? One possibility here is that there is an improvement in response latency, rather than perceptual sensitivity. Is there any hint of that in the RT results? In some sort of combined measure of RT and accuracy? 

      First, we would like to thank the reviewer for their positive assessment of our work and for their extremely helpful and constructive comments that helped to significantly improve the quality of our manuscript.  

      The reviewer rightly points out that, to our surprise, we did not obtain a correlate of the effect of memantine in our behavioral data, neither in the reported accuracy data nor in the RT data. We do not report RT results as participants were instructed to respond as accurately as possible, without speed pressure. We added a paragraph in the discussion section to point to possible reasons for this surprising finding:

      “There are several possible reasons for this lack of behavioral correlate.  For example, EEG decoding may be a more sensitive measure of the neural effects of memantine, in particular given that perceptual sensitivity may have been at floor (masked condition, experiment 1) or ceiling (unmasked condition, experiment 1, and experiment 2). It is also possible that the present decoding results are merely epiphenomenal, not mapping onto functional improvements (e.g., Williams et al., 2007). However, given that we found a tight link between these EEG decoding markers and behavioral performance in our previous work (Fahrenfort et al., 2017; Noorman et al., 2023), it is possible that the effect of memantine was just too subtle to show up in changes in overt behavior.”

      (2) An explanation is missing, about why memantine impacts the decoding of illusion but not collinearity. At a systems level, how would this work? How would NMDAR antagonism selectively impact long-range connectivity, but not lateral connectivity? Is this supported by our understanding of laminar connectivity and neurochemistry in the visual cortex?

      We have no straightforward or mechanistic explanation for this finding. In the revised discussion, we are highlighting this finding more clearly, and included some speculative explanations:

      “The present effect of memantine was largely specific to illusion decoding, our marker of feedback processing, while collinearity decoding, our marker of lateral processing, was not (experiment 1) or only weakly (experiment 2) affected by memantine. We have no straightforward explanation for why NMDA receptor blockade would impact inter-areal feedback connections more strongly than intra-areal lateral connections, considering their strong functional interdependency and interaction in grouping and segmentation processes (Liang et al., 2017). One possibility is that this finding reflects properties of our EEG decoding markers for feedback vs. lateral processing: for example, decoding of the Kanizsa illusion may have been more sensitive to the relatively subtle effect of our pharmacological manipulation, either because overall decoding was better than for collinearity or because NMDA receptor dependent recurrent processes more strongly contribute to illusion decoding than to collinearity decoding.”

      (3) The motivating idea for the paper is that the NMDAR antagonist might disrupt the modulation of the AMPA-mediated glu signal. This is in line with the motivating logic for Self et al., 2012, where NMDAR and AMPAR efficacy in macacque V1 was manipulated via microinfusion. But this logic seems to conflict with a broader understanding of NMDA antagonism. NMDA antagonism appears to generally have the net effect of increasing glu (and ACh) in the cortex through a selective effect on inhibitory GABAergic cells (eg. Olney, Newcomer, & Farber, 1999). Memantine, in particular, has a specific impact on extrasynaptic NMDARs (that is in contrast to ketamine; Milnerwood et al, 2010, Neuron), and this type of receptor is prominent in GABA cells (eg. Yao et al., 2022, JoN). The effect of NMDA antagonists on GABAergic cells generally appears to be much stronger than the effect on glutamergic cells (at least in the hippocampus; eg. Grunze et al., 1996).

      This all means that it's reasonable to expect that memantine might have a benefit to visually evoked activity. This idea is raised in the GD of the paper, based on a separate literature from that I mentioned above. But all of this could be better spelled out earlier in the paper, so that the result observed in the paper can be interpreted by the reader in this broader context.

      To my mind, the challenging task is for the authors to explain why memantine causes an increase in EEG decoding, where microinfusion of an NMDA antagonist into V1 reduced the neural signal Self et al., 2012. This might be as simple as the change in drug... memantine's specific efficacy on extrasynaptic NMDA receptors might not be shared with whatever NMDA antagonist was used in Self et al. 2012. Ketamine and memantine are already known to differ in this way. 

      We addressed the reviewer’s comments in the following way. First, we bring up our (to us, surprising) result already at the end of the Introduction, pointing the reader to the explanation mentioned by the reviewer:

      “We hypothesized that disrupting the reentrant glutamate signal via blocking NMDA receptors by memantine would impair illusion and possibly collinearity decoding, as putative markers of feedback and lateral processing, but would spare the decoding of local contrast differences, our marker of feedforward processing. To foreshadow our results, memantine indeed specifically affected illusion decoding, but enhancing rather than impairing it. In the Discussion, we offer explanations for this surprising finding, including the effect of memantine on extrasynaptic NMDA receptors in GABAergic cells, which may have resulted in boosted visual activity.”

      Second, as outlined in the response to the first point by Reviewer #2, we are now clear throughout the title, abstract, and paper that memantine “improved” rather than “modulated” illusion decoding.

      Third, and most importantly, we restructured and expanded the Discussion section to include the reviewer’s proposed mechanisms and explanations for the effect. We would like to thank the reviewer for pointing us to this literature. We also discuss the results of Self et al. (2012), specifically the distinct effects of the two NMDAR antagonists used in this study, more extensively, and speculate that their effects may have been similar to ketamine and thus possibly opposite of memantine (for the feedback signal):

      “Although both drugs are known to inhibit NMDA receptors by occupying the receptor’s ion channel and are thereby blocking current flow (Glasgow et al., 2017; Molina et al., 2020), the drugs have different actions at receptors other than NMDA, with ketamine acting on dopamine D2 and serotonin 5-HT2 receptors, and memantine inhibiting several subtypes of the acetylcholine (ACh) receptor as well as serotonin 5HT3 receptors. Memantine and ketamine are also known to target different NMDA receptor subpopulations, with their inhibitory action displaying different time courses and intensity (Glasgow et al., 2017; Johnson et al., 2015). Blockade of different NMDA receptor subpopulations can result in markedly different and even opposite results. For example, Self and colleagues (2012) found overall reduced or elevated visual activity after microinfusion of two different selective NMDA receptor antagonists (2-amino-5phosphonovalerate and ifendprodil) in macaque primary visual cortex. Although both drugs impaired the feedback-related response to figure vs. ground, similar to the effects of ketamine (Meuwese et al., 2013; van Loon et al., 2016) such opposite effects on overall activity demonstrate that the effects of NMDA antagonism strongly depend on the targeted receptor subpopulation, each with distinct functional properties.”

      Finally, we link these differences to the potential mechanism via GABAergic neurons:

      “As mentioned in the Introduction, this may be related to memantine modulating processing at other pre- or post-synaptic receptors present at NMDA-rich synapses, specifically affecting extrasynaptic NMDA receptors in GABAergic cells (Milnerwood et al, 2010; Yao et al., 2022). Memantine’s strong effect on extrasynaptic NMDA receptors in GABAergic cells leads to increases in ACh levels, which have been shown to increase firing rates and reduce firing rate variability in macaques (Herrero et al., 2013, 2008). This may represent a mechanism through which memantine (but not ketamine or the NMDA receptor antagonists used by Self and colleagues) could boost visually evoked activity.”

      (4) The paper's proposal is that the effect of memantine is mediated by an impact on the efficacy of reentrant signaling in visual cortex. But perhaps the best-known impact of NMDAR manipulation is on LTP, in the hippocampus particularly but also broadly.

      Perception and identification of the kanisza illusion may be sensitive to learning (eg. Maertens & Pollmann, 2005; Gellatly, 1982; Rubin, Nakayama, Shapley, 1997); what argues against an account of the results from an effect on perceptual learning? Generally, the paper proposes a very specific mechanism through which the drug influences perception. This is motivated by results from Self et al 2012 where an NMDA antagonist was infused into V1. But oral memantine will, of course, have a whole-brain effect, and some of these effects are well characterized and - on the surface - appear as potential sources of change in illusion perception. The paper needs some treatment of the known ancillary effects of diffuse NMDAR antagonism to convince the reader that the account provided is better than the other possibilities. 

      We cannot fully exclude an effect based on perceptual learning but consider this possibility highly unlikely for several reasons. First, subjects have performed more than a thousand trials in a localizer session before starting the main task (in experiment 2 even more than two thousand) containing the drug manipulation. Therefore, a large part of putative perceptual learning would have already occurred before starting the main experiment. Second, the main experiment was counterbalanced across drug sessions, so half of the participants first performed the memantine session and then the placebo session, and the other half of the subjects the other way around. If memantine would have improved perceptual learning in our experiments, one may actually expect to observe improved decoding in the placebo session and not in the memantine session. If memantine would have facilitated perceptual learning during the memantine session, the effect of that facilitated perceptual learning would have been most visible in the placebo session following the memantine session. Because we observed improved decoding in the memantine session itself, perceptual learning is likely not the main explanation for these findings. Third, perceptual learning is known to occur for several stimulus dimensions (e.g., orientation, spatial frequency or contrast). If these findings would have been driven by perceptual learning one would have expected to see perceptual learning for all three features, whereas the memantine effects were specific to illusion decoding. Especially in experiment 2, all features were equally often task relevant and in such a situation one would’ve expected to observe perceptual learning effects on those other features as well.  

      To further investigate any potential role of perceptual learning, we analyzed participants’ performance in detecting the Kanizsa illusion over the course of the experiments. To investigate this, we divided the experiments’ trials into four time bins, from the beginning until the end of the experiment. For the first experiment’s first target (T1), there was no interaction between the factors bin and drug (memantine/placebo; F<sub>3,84</sub>=0.89, P\=0.437; Figure S6A). For the second target (T2), we performed a repeatedmeasures ANOVA with the factors bin, drug, T1-T2 lag (short/long), and masks (present/absent). There was only a trend towards a bin by drug interaction (F<sub>3,84</sub>=2.57, P\=0.064; Figure S6B), reflecting worse performance under memantine in the first three bins and slightly better performance in the fourth bin. The other interactions that include the factors bin and drug factors were not significant (all P>0.117). For the second experiment, we performed a repeated-measures ANOVA with the factors bin, drug, masks, and task-relevant feature (local contrast/collinearity/illusion). None of the interactions that included the bin and drug factors were significant (all P>0.219; Figure S6C). Taken together, memantine does not appear to affect Kanizsa illusion detection performance through perceptual learning. Finally, there was no interaction between the factors bin and task-relevant feature (F<sub>6,150</sub>=0.76, P\=0.547; Figure S6D), implying there is no perceptual learning effect specific to Kanizsa illusion detection. We included these analyses in our revised Supplement as Fig. S6.

      (5) The cross-decoding approach to data analysis concerns me a little. The approach adopted here is to train models on a localizer task, in this case, a task where participants matched a kanisza figure to a target template (E1) or discriminated one of the three relevant stimuli features (E2). The resulting model was subsequently employed to classify the stimuli seen during separate tasks - an AB task in E1, and a feature discrimination task in E2. This scheme makes the localizer task very important. If models built from this task have any bias, this will taint classifier accuracy in the analysis of experimental data. My concern is that the emergence of the kanisza illusion in the localizer task was probably quite salient, respective to changes in stimuli rotation or collinearity. If the model was better at detecting the illusion to begin with, the data pattern - where drug manipulation impacts classification in this condition but not other conditions - may simply reflect model insensitivity to non-illusion features.

      I am also vaguely worried by manipulations implemented in the main task that do not emerge in the localizer - the use of RSVP in E1 and manipulation of the base rate and staircasing in E2. This all starts to introduce the possibility that localizer and experimental data just don't correspond, that this generates low classification accuracy in the experimental results and ineffective classification in some conditions (ie. when stimuli are masked; would collinearity decoding in the unmasked condition potentially differ if classification accuracy were not at a floor? See Figure 3c upper, Figure 5c lower).

      What is the motivation for the use of localizer validation at all? The same hypotheses can be tested using within-experiment cross-validation, rather than validation from a model built on localizer data. The argument may be that this kind of modelling will necessarily employ a smaller dataset, but, while true, this effect can be minimized at the expense of computational cost - many-fold cross-validation will mean that the vast majority of data contributes to model building in each instance. 

      It would be compelling if results were to reproduce when classification was validated in this kind of way. This kind of analysis would fit very well into the supplementary material.

      We thank the reviewer for this excellent question. We used separate localizers for several reasons, exactly to circumvent the kind of biases in decoding that the reviewer alludes to. Below we have detailed our rationale, first focusing on our general rationale and then focusing on the decisions we made in designing the specific experiments.  

      Using a localizer task in the design of decoding analysis offers several key advantages over relying solely on k-fold cross-validation within the main task:

      (1) Feature selection independence and better generalization: A separate localizer task allows for independent feature selection, ensuring that the features used for decoding are chosen without bias from the main task data. Specifically, the use of a localizer task allows us to determine the time-windows of interest independently based on the peaks of the decoding in the localizer. This allows for a better direct comparison between the memantine and placebo conditions because we can isolate the relevant time windows outside a drug manipulation. Further, training a classifier on a localizer task and testing it on a separate experimental task assesses whether neural representations generalize across contexts, rather than simply distinguishing conditions within a single dataset. This supports claims about the robustness of the decoded information.

      (2) Increased sensitivity and interpretability: The localizer task can be designed specifically to elicit strong, reliable responses in the relevant neural patterns. This can improve signal-to-noise ratio and make it easier to interpret the features being used for decoding in the test set. We facilitate this by having many more trials in the localizer tasks (1280 in E1 and 5184 in E2) than in the separate conditions of the main task, in which we would have to do k-folding (e.g., 2, mask, x 2 (lag) design in E1 leaves fewer than 256 trials, due to preprocessing, for specific comparisons) on very low trial numbers. The same holds for experiment 2 which has a 2x3 design, but also included the base-rate manipulation. Finally, we further facilitate sensitivity of the model by having the stimuli presented at full contrast without any manipulations of attention or masking during the localizer, which allows us to extract the feature specific EEG signals in the most optimal way.

      (3) Decoupling task-specific confounds: If decoding is performed within the main task using k-folding, there is a risk that task-related confounds (e.g., motor responses, attention shifts, drug) influence decoding performance. A localizer task allows us to separate the neural representation of interest from these taskrelated confounds.

      Experiment 1 

      In experiment 1, the Kanizsa was always task relevant in the main experiment in which we employed the pharmacological manipulation. To make sure that the classifiers were not biased towards Kanizsa figures from the start (which would be the case if we would have done k-folding in the main task), we used a training set in which all features were equally relevant for task performance. As can be seen in figure 1E, which plots the decoding accuracies of the localizer task, illusion decoding as well as rotation decoding were equally strong, whereas collinearity decoding was weaker. It may be that the Kanizsa illusion was quite salient in the localizer task, which we can’t know at present, but it was at least less salient and relevant than in the main task (where it was the only task-relevant feature). Based on the localizer decoding results one could argue that the rotation dimension and illusion dimension were most salient, because the decoding was highest for these dimensions. Clearly the model was not insensitive to nonillusory features. The localizer task of experiment 2 reveals that collinearity decoding tends to be generally lower, even when that feature is task relevant.  

      Experiment 2 

      In experiment 2, the localizer task and main task were also similar, with three exceptions: during the localizer task no drug was active, and no masking and no base rate manipulation were employed. To make sure that the classifier was not biased towards a certain stimulus category (due to the bias manipulation), e.g. the stimulus that is presented most often, we used a localizer task without this manipulation. As can be seen in figure 4D decoding of all the features was highly robust, also for example for the collinearity condition. Therefore the low decoding that we observe in the main experiment cannot be due to poor classifier training or feature extraction in the localizer. We believe this is actually an advantage instead of a disadvantage of the current decoding protocol.

      Based on the rationale presented above we are uncomfortable performing the suggested analyses using a k-folding approach in the main task, because according to our standards the trial numbers are too low and the risk that these results are somehow influenced by task specific confounds cannot be ruled out.  

      Line 301 - 'Interestingly, in both experiments the effect of memantine... was specific to... stimuli presented without a backward mask.' This rubs a bit, given that the mask broadly disrupted classification. The absence of memantine results in masked results may simply be a product of the floor ... some care is needed in the interpretation of this pattern. 

      In the results section of experiment 1, we added:

      “While the interaction between masking and memantine only approached significance (P\=0.068), the absence of an effect of memantine in the masked condition could reflect a floor effect, given that illusion decoding in the masked condition was not significantly better than chance.”

      While floor is less likely to account for the absence of an effect in the masked condition in experiment 2, where illusion decoding in the masked condition was significantly above chance, it is still possible that to obtain an effect of memantine, decoding accuracy needed to be higher. We therefore also added here:

      “For our time window-based analyses of illusion decoding, the specificity of the memantine effect to the unmasked condition was supported by a significant interaction between drug and masking (note, however, given overall much lower decoding accuracy in the masked condition, the lack of a memantine effect could reflect a floor effect).”

      In the discussion, we changed the sentence to read “…the effect of memantine on illusion decoding tended to be specific to attended, task-relevant stimuli presented without a backward mask.”

      Line 441 - What were the contraindications/exclusion parameters for the administration of memantine? 

      Thanks for spotting this. We have added the relevant exclusion criteria in the revised version of the supplement. See also below.

      – Allergy for memantine or one of the inactive ingredients of these products;

      – (History of) psychiatric treatment;

      – First-degree relative with (history of) schizophrenia or major depression;

      – (History of) clinically significant hepatic, cardiac, obstructive respiratory, renal, cerebrovascular, metabolic or pulmonary disease, including, but not limited to fibrotic disorders;

      – Claustrophobia;

      –  Regular usage of medicines (antihistamines or occasional use of paracetamol);

      – (History of) neurological disease;

      –  (History of) epilepsy;

      –  Abnormal hearing or (uncorrected) vision;

      –  Average use of more than 15 alcoholic beverages weekly;

      – Smoking

      – History of drug (opiate, LSD, (meth)amphetamine, cocaine, solvents, cannabis, or barbiturate) or alcohol dependence;

      – Any known other serious health problem or mental/physical stress;

      – Used psychotropic medication, or recreational drugs over a period of 72 hours prior to each test session,  

      – Used alcohol within the last 24 hours prior to each test session;

      – (History of) pheochromocytoma.

      – Narrow-angle glaucoma;

      – (History of) ulcer disease;

      – Galactose intolerance, Lapp lactase deficiency or glucose­galactose malabsorption.

      – (History of) convulsion;

      Line 587 - The localizer task used to train the classifier in E2 was collected in different sessions. Was the number of trials from separate sessions ultimately equal? The issue here is that the localizer might pick up on subtle differences in electrode placement. If the test session happens to have electrode placement that is similar to the electrode placement that existed for a majority of one condition of the localizer... this will create bias. This is likely to be minor, but machine classifiers really love this kind of minor confound.

      Indeed, the trial counts in the separate sessions for the localizer in E2 were equal. We have added that information to the methods section.  

      Experiment 1: 1280 trials collected during the intake session.

      In experiment 2: 1728 trials were collected per session (intake, and 2 drug sessions), so there were 5184 trials across three sessions.

      Reviewer #2:

      To start off, I think the reader is being a bit tricked when reading the paper. Perhaps my priors are too strong, but I assumed, just like the authors, that NMDA-receptors would disrupt recurrent processing, in line with previous work. However, due to the continuous use of the ambiguous word 'affected' rather than the more clear increased or perturbed recurrent processing, the reader is left guessing what is actually found. That's until they read the results and discussion finding that decoding is actually improved. This seems like a really big deal, and I strongly urge the authors to reword their title, abstract, and introduction to make clear they hypothesized a disruption in decoding in the illusion condition, but found the opposite, namely an increase in decoding. I want to encourage the authors that this is still a fascinating finding.

      We thank the reviewer for the positive assessment of our manuscript, and for many helpful comments and suggestions.  

      We changed the title, abstract, and introduction in accordance with the reviewer’s comment, highlighting that “memantine […] improves decoding” and “enhances recurrent processing” in all three sections. We also changed the heading of the corresponding results section to “Memantine selectively improves decoding of the Kanizsa illusion”.

      Apologies if I have missed it, but it is not clear to me whether participants were given the drug or placebo during the localiser task. If they are given the drug this makes me question the logic of their analysis approach. How can one study the presence of a process, if their very means of detecting that process (the localiser) was disrupted in the first place? If participants were not given a drug during the localiser task, please make that clear. I'll proceed with the rest of my comments assuming the latter is the case. But if the former, please note that I am not sure how to interpret their findings in this paper.

      Thanks for asking this, this was indeed unclear. In experiment 1 the localizer was performed in the intake session in which no drugs were administered. In the second experiment the localizer was performed in all three sessions with equal trial numbers. In the intake session no drugs were administrated. In the other two sessions the localizer was performed directly after pill intake and therefore the memantine was not (or barely) active yet. We started the main task four hours after pill intake because that is the approximate peak time of memantine. Note that all three localizer tasks were averaged before using them as training set. We have clarified this in the revised manuscript.

      The main purpose of the paper is to study recurrent processing. The extent to which this study achieves this aim is completely dependent to what extent we can interpret decoding of illusory contours as uniquely capturing recurrent processing. While I am sure illusory contours rely on recurrent processing, it does not follow that decoding of illusory contours capture recurrent processing alone. Indeed, if the drug selectively manipulates recurrent processing, it's not obvious to me why the authors find the interaction with masking in experiment 2. Recurrent processing seems to still be happening in the masked condition, but is not affected by the NMDA-receptor here, so where does that leave us in interpreting the role of NMDA-receptors in recurrent processing? If the authors can not strengthen the claim that the effects are completely driven by affecting recurrent processing, I suggest that the paper will shift its focus to making claims about the encoding of illusory contours, rather than making primary claims about recurrent processing.

      We indeed used illusion decoding as a marker of recurrent processing. Clearly, such a marker based on a non-invasive and indirect method to record neural activity is not perfect. To directly and selectively manipulate recurrent processing, invasive methods and direct neural recordings would be required. However, as explained in the revised Introduction,

      “In recent work we have validated that the decoding profiles of these features of different complexities at different points in time, in combination with the associated topography, can indeed serve as EEG markers of feedforward, lateral and recurrent processes (Fahrenfort et al., 2017; Noorman et al., 2023).”  

      The timing and topography of the decoding results of the present study were consistent with our previous EEG decoding studies (Fahrenfort et al., 2017; Noorman et al., 2023). This validates the use of these EEG decoding signatures as (imperfect) markers of distinct neural processes, and we continue to use them as such. However, we expanded the discussion section to alert the reader to the indirect and imperfect nature of these EEG decoding signatures as markers of distinct neural processes: “Our approach relied on using EEG decoding of different stimulus features at different points in time, together with their topography, as markers of distinct neural processes. Although such non-invasive, indirect measures of neural activity cannot provide direct evidence for feedforward vs. recurrent processes, the timing, topography, and susceptibility to masking of the decoding signatures obtained in the present study are consistent with neurophysiology (e.g., Bosking et al., 1997; Kandel et al., 2000; Lamme & Roelfsema, 2000; Lee & Nguyen, 2001; Liang et al., 2017; Pak et al., 2020), as well as with our previous work (Fahrenfort et al., 2017; Noorman et al., 2023).” 

      The reviewer is also concerned about the lack of effect of memantine on illusion decoding in the masked condition in experiment 2. In our view, the strong effect of masking on illusion decoding (both in absolute terms, as well as when compared to its effect on local contrast decoding), provides strong support for our assumption that illusion decoding represents a marker of recurrent processing. Nevertheless, as the reviewer points out, weak but statistically significant illusion decoding was still possible in the masked condition, at least when the illusion was task-relevant. As the reviewer notes, this may reflect residual recurrent processing during masking, a conclusion consistent with the relatively high behavioral performance despite masking (d’ > 1). However, rather than invalidating the use of our EEG markers or challenging the role of NMDA-receptors in recurrent processing, this may simply reflect a floor effect. As outlined in our response to reviewer #1 (who was concerned about floor effects), in the results section of experiment 1, we added:

      “While the interaction between masking and memantine only approached significance (P\=0.068), the absence of an effect of memantine in the masked condition could reflect a floor effect, given that illusion decoding in the masked condition was not significantly better than chance.”

      And for experiment 1:

      “For our time window-based analyses of illusion decoding, the specificity of the memantine effect to the unmasked condition was supported by a significant interaction between drug and masking (note, however, given overall much lower decoding accuracy in the masked condition, the lack of a memantine effect could reflect a floor effect).”

      An additional claim is being made with regards to the effects of the drug manipulation. The authors state that this effect is only present when the stimulus is 1) consciously accessed, and 2) attended. The evidence for claim 1 is not supported by experiment 1, as the masking manipulation did not interact in the cluster-analyses, and the analyses focussing on the peak of the timing window do not show a significant effect either. There is evidence for this claim coming from experiment 2 as masking interacts with the drug condition. Evidence for the second claim (about task relevance) is not presented, as there is no interaction with the task condition. A classical error seems to be made here, where interactions are not properly tested. Instead, the presence of a significant effect in one condition but not the other is taken as sufficient evidence for an interaction, which is not appropriate. I therefore urge the authors to dampen the claim about the importance of attending to the decoded features. Alternatively, I suggest the authors run their interactions of interest on the time-courses and conduct the appropriate clusterbased analyses.

      We thank the reviewer for pointing out the importance of key interaction effects. Following the reviewer’s suggestion, we dampened our claims about the role of attention. For experiment 1, we changed the heading of the relevant results section from “Memantine’s effect on illusion decoding requires attention” to “The role of consciousness and attention in memantine’s effect on illusion decoding”, and we added the following in the results section:

      “Also our time window-based analyses showed a significant effect of memantine only when the illusion was both unmasked and presented outside the AB (t_28\=-2.76, _P\=0.010, BF<sub>10</sub>=4.53; Fig. 3F). Note, however, that although these post-hoc tests of the effect of memantine on illusion decoding were significant, for our time window-based analyses we did not obtain a statistically significant interaction between the AB and memantine, and the interaction between masking and memantine only approached significance (P\= 0.068). Thus, although these memantine effects were slightly less robust than for T1, probably due to reduced trial counts, these results point to (but do not conclusively demonstrate) a selective effect of memantine on illusion-related feedback processing that depends on the availability of attention. In addition to the lack of the interaction effect, another potential concern…”

      For experiment 2, we added the following in the results section:

      “Note that, for our time window-based analyses of illusion decoding, although the specificity of the memantine effect to the unmasked condition was supported by a significant interaction between drug and masking, we did not obtain a statistically significant interaction between memantine and task-relevance. Thus, although the memantine effect was significant only when the illusion was unmasked and taskrelevant, just like for the effect of temporal attention in experiment 1, these results do not conclusively demonstrate a selective effect of memantine that depends attention (task-relevance).”

      In the discussion, we toned down claims about memantine’s effects being specific to attended conditions, we are highlighting the “preliminary” nature of these findings, and we are now alerting the reader explicitly to be careful with interpreting these effects, e.g.:

      “Although these results have to be interpreted with caution because the key interaction effects were not statistically significant, …”

      How were the length of the peak-timing windows established in Figure 1E? My understanding is that this forms the training-time window for the further decoding analyses, so it is important to justify why they have different lengths, and how they are determined. The same goes for the peak AUC time windows for the interaction analyses. A number of claims in the paper rely on the interactions found in these posthoc analyses, so the 223- to 323 time window needs justification.

      Thanks for this question. The length of these peak-timing windows is different because the decoding of rotation is temporarily very precise and short-lived, whereas the decoding of the other features last much longer and is more temporally variable. In fact, we have followed the same procedure as in a previously published study (Noorman et al., elife 2025) for defining the peak-timing and length of the windows. We followed the same procedure for both experiments reported in this paper, replicating the crucial findings and therefore excluding the possibility that these findings are in any way dependent on the time windows that are selected. We have added that information to the revised version of the manuscript.

      Reviewer #3:

      First, despite its clear pattern of neural effects, there is no corresponding perceptual effect. Although the manipulation fits neatly within the conceptual framework, and there are many reasons for not finding such an effect (floor and ceiling effects, narrow perceptual tasks, etc), this does leave open the possibility that the observation is entirely epiphenomenal, and that the mechanisms being recorded here are not actually causally involved in perception per se.

      We thank the reviewer for the positive assessment of our work. The reviewer rightly points out that, to our surprise, we did not obtain a correlate of the effect of memantine in our behavioral data. We agree with the possible reasons for the absence of such an effect highlighted by the reviewer, and expanded our discussion section accordingly:

      “There are several possible reasons for this lack of behavioral correlate.  For example, EEG decoding may be a more sensitive measure of the neural effects of memantine, in particular given that perceptual sensitivity may have been at floor (masked condition, experiment 1) or ceiling (unmasked condition, experiment 1, and experiment 2). It is also possible that the present decoding results are merely epiphenomenal, not mapping onto functional improvements (e.g., Williams et al., 2007). However, given that in our previous work we found a tight link between these EEG decoding markers and behavioral performance (Fahrenfort et al., 2017; Noorman et al., 2023), it is possible that the effect of memantine in the present study was just too subtle to show up in changes in overt behavior.”

      Second, although it is clear that there is an effect on decoding in this particular condition, what that means is not entirely clear - particularly since performance improves, rather than decreases. It should be noted here that improvements in decoding performance do not necessarily need to map onto functional improvements, and we should all be careful to remain agnostic about what is driving classifier performance. Here too, the effect of memantine on decoding might be epiphenomenal - unrelated to the information carried in the neural population, but somehow changing the balance of how that is electrically aggregated on the surface of the skull. *Something* is changing, but that might be a neurochemical or electrical side-effect unrelated to actual processing (particularly since no corresponding behavioural impact is observed.)

      We would like to refer to our reply to the previous point, and we would like to add that in our previous work (Fahrenfort et al., 2017; Noorman et al., 2023) similar EEG decoding markers were often tightly linked to changes in behavioral performance. This indicates that these particular EEG decoding markers do not simply reflect some sideeffect not related to neural processing. However, as stated in the revised discussion section, “it is possible that the effect of memantine in the present study was just too subtle to show up in changes in overt behavior.”

    1. Author response:

      The following is the authors’ response to the original reviews

      Reviewer #1 (Public Review):

      (…) In my view, the part about NF-YA1 is less strong - although I realize this is a compelling candidate to be a regulator of cell cycle progression, the experimental approaches used to address this question falls a bit short, in particular, compared to the very detailed approaches shown in the rest of the manuscript. The authors show that the transcription factor NF-YA1 regulates cell division in tobacco leaves; however, there is no experimental validation in the experimental system (nodules). All conclusions are based on a heterologous cell division system in tobacco leaves. The authors state that NF-YA1 has a nodule-specific role as a regulator of cell differentiation. I am concerned the tobacco system may not allow for adequate testing of this hypothesis.

      Reviewer #1 makes a valid point by asking to focus the manuscript more explicitly on the role of NF-YA1 as a differentiation factor in a symbiotic context. We have now addressed this formally and experimentally.

      The involvement of A-type NF-Y subunits in the transition to the early differentiation of nodule cells has been documented in model legumes through several publications that we refer to in the revised version of the discussion (lines 617/623). We fully agree that the CDEL system, because it is heterologous, does not allow us more than to propose a parallel explanation for these observations - i.e_., that the Medicago NF-YA1 subunit presumably acts in post-replicative cell-cycle regulation at the G2/M transition. Considering your recommendations and those of reviewer #2, we sought to support this conclusion by testing the impact of localized over-expression of _NF-YA1 on cortical cell division and infection competence at an early stage of root colonization. The results of these experiments are now presented in the new Figure 9 and Figure 9-figure supplement 1-5 and described from line 435 to 495.

      With the fluorescent tools the authors have at hand (in particular tools to detect G2/M transition, which the authors suggest is regulated by NF-YA1), it would be interesting to test what happens to cell division if NF-YA1 is over-expressed in Medicago roots?

      To limit pleiotropic effects of an ectopic over-expression, we used the symbiosis-induced, ENOD11 promoter to increase NF-YA1 expression levels more specifically along the trajectory of infected cells. We chose to remain in continuity with the experiments performed in the CDEL system by opting for a destabilized version of the KNOLLE transcriptional reporter to detect the G2/M transition. The results obtained are presented in Figure 9B (quantification of split infected cells), in Figure 9-figure supplement 1B (ENOD11 expression profile), in Figure 9-figure supplement 3B (representative confocal images) and Figure 9-figure supplement 4D (quantification of pKNOLLE reporter signal). There, we show that mitosis remains inhibited in cells accommodating infection threads, but is completed in a higher proportion of outer cortical cells positioned on the infection trajectory, where ENOD11 gene transcription is active before their physical colonization.

      Based on NF-YA1 expression data published previously and their results in tobacco epidermal cells, the authors hypothesize that NF-YA regulates the mitotic entry of nodule primordial cells. Given that much of the manuscript deals with earlier stages of the infection, I wonder if NF-YA1 could also have a role in regulating mitotic entry in cells adjacent to the infection thread?

      The expression profile of NF-YA1 at early stages of cortical infection (Laporte et al., 2014) is indeed similar to the one of ENOD11 (as shown in Figure 9-figure supplement 1C) in wild-type Medicago roots, with corresponding transcriptional reporters being both activated in cells adjacent to the infection thread. Under our experimental conditions, additional expression of NF-YA1 (driven by the ENOD11 promoter) in these neighbouring cells did not impact their propensity to enter mitosis and to complete cell division. These results are presented in Figure 9-figure supplement 4D (quantification of pKNOLLE reporter signal) and Figure 9-figure supplement 5 (quantification of split neighbouring cells).

      Reviewer #1 (Recommendations For The Authors):

      - In the first part, images show the qualitative presence/absence of H3.1 or H3.3 histones.

      Upon closer inspection, many cells seem to have both histones. In Fig1-S1 for example (root meristem), it is evident that there are many cells with low but clearly present H3.1 content in the green channel; however, in the overlay, the green is lost and H3.3 (pink) is mainly visible. What does this mean in terms of the cell cycle? 

      We fully agree with reviewer #1 on these points. Independent of whether they have low or high proliferation potential, most cells retain histone H3.1 particularly in silent regions of the genome, while H3.3 is constitutively produced and enriched at transcriptionally active regions. When channels are overlaid, cells in an active proliferation or endoreduplication state (in G1, S or G2, depending on the size of their nuclei) will appear mainly "green" (H3.1-eGFP positive). Cells with a low proliferation potential (e.g., in the QC), G2-arrested (e.g., IT-traversed) or terminally differentiating (e.g., containing symbiosomes or arbuscules) will appear mainly "magenta" (H3.1-low, medium to high H3.3-mCherry content).

      Furthermore, all nodule images only display the overlay image, and individual fluorescence channels are not shown. Does the same masking effect happen here? It may be helpful to quantify fluoresce intensity not only in green but also in red channels as done for other experiments.

      Quantifying fluorescence intensity in the mCherry channel may indeed help to highlight the likely replacement of H3.1-eGFP by H3.3-mCherry in infected cells, as described by Otero and colleagues (2016) at the onset of cellular differentiation. However, the quantification method as established (i.e., measuring the corrected total nuclear fluorescence at the equatorial plane) cannot be applied, most of the time, to infected cells' nuclei due to the overlapping presence of mCherry-producing S. meliloti in the same channel (e.g., in Figure 2B). Nevertheless, and to avoid this masking effect when the eGFP and mCherry channels are overlaid, we now present them as isolated channels in revised Figures 1-3 and associated figure supplements. As the cell-wall staining is regularly included and displayed in grayscale, we assigned to both of them the Green Fire Blue lookup table, which maps intensity values to a multiple-colour sequential scheme (with blue or yellow indicating low or high fluorescence levels, respectively). We hope that this will allow a better appreciation of the respective levels of H3.1- and H3.3-fusions in our confocal images.

      - Fig 1 B - it is hard to differentiate between S. meliloti-mCherry and H3.3-mCherry. Is there a way to label the different structures?

      In the revised version of Figure 1B, we used filled or empty arrowheads to point to histone H3-containing nuclei. To label rhizobia-associated structures, we used dashed lines to delineate nodule cells hosting symbiosomes and included the annotation “IT” for infection threads. We also indicated proliferating, endoreduplicating and differentiating tissues and cells using the following annotations: “CD” for cell division, “En” for endoreduplication and “TD” for terminal differentiation. All annotations are explained in the figure legend.

      - Fig 1 - supplement E and F - no statistics are shown.

      We performed non-parametric tests using the latest version of the GraphPad Prism software (version 10.4.1). Stars (Figure 1-figure supplement 1F) or different letters (Figure 1-figure supplement 1G) now indicate statistically significant differences. Results of the normality and non-parametric tests were included in the corresponding Source Data Files (Figure 1 – figure supplement 1 – source data 1 and 2). We have also updated the compact display of letters in other figures as indicated by the new software version. The raw data and the results of the statistical analyses remain unchanged and can be viewed in the corresponding source files.

      - Fig 2 A - overview and close-up image do not seem to be in the same focal plane. This is confusing because the nuclei position is different (so is the infection thread position).

      We fully agree that our former Figure may have confused reviewers #1 and #2 as well as readers. Figure 2A was designed to highlight, from the same nodule primordium, actively dividing cells of the inner cortex (optical section z 6-14) and cells of the outer cortex traversed, penetrated by or neighbouring an infection thread (optical section z 11-19). We initially wanted to show different magnification views of the same confocal image (i.e_._, a full-view of the inner cortex and a zoomed-view of the outer layers) to ensure that audiences can identify these details. In the revised version of Figure 2A, we displayed these full- and zoomed-views in upper and lower panels, respectively and we removed the solid-line inset to avoid confusion. 

      - Fig 1A and Fig 2E could be combined and shown at the beginning of the manuscript. Also, consider making the cell size increase more extreme, as it is important to differentiate G2 cells after H3.1 eviction and cells in G1. You have to look very closely at the graph to see the size differences.

      We have taken each of your suggestions into account. A combined version of our schematic representation with more pronounced nuclei size differences is now presented in Figure 1A.

      - Fig. 3 C is difficult to interpret. Can this be split into different panels?

      We realized that our previous choice of representation may have been confusing. Each value corresponds only to the H3.1-eGFP content, measured in an infected cell and reported to that of the neighbouring cell (IC / NC) within individual root samples. Therefore, we removed the green-magenta colour code and changed the legend accordingly. We hope that these slight modifications will facilitate the interpretation of the results - namely, that the relative level of H3.1 increases significantly in infected cells in the selected mutants compared to the wild-type. This mode of representation also highlights that in the mutants, there are more individual cases where the H3.1 content in an infected cell exceeds that of the neighbouring cell by more than two times. These cases would be masked if the couples of infected cells and associated neighbours would be split into different panels as in Figure 3B.

      - Line 357/359. I assume you mean ...'through the G2 phase can commit to nuclear division'.

      We have edited this sentence according to your suggestion, which now appears in line 370. 

      Reviewer #2 (Recommendations For The Authors):

      Cell cycle control during the nitrogen-fixing symbiosis is an important question but only poorly understood. This manuscript uses largely cell biological methods, which are always of the highest quality - to investigate host cell cycle progression during the early stages of nodule formation, where cortical infection threads penetrate the nodule primordium. The experiments were carefully conducted, the observations were detail oriented, and the results were thought-provoking. The study should be supported by mechanistic insights. 

      (1) One thought provoked by the authors' work is that while the study was carried out at an unprecedented resolution, the relationship between control of the cell cycle and infection thread penetration remains correlative. Is this reduced replicative potential among cells in the infection thread trajectory a consequence of hosting an infection thread, or a prerequisite to do so?

      We understand and share the point of view of reviewer #2. At this stage, we believe that our data won’t enable us to fully answer the question, thus this relationship remains rather correlative. The reasons are that 1) the access to the status of cortical cells below C2 is restricted to fixed material and therefore only represents a snapshot of the situation, and 2) we are currently unable to significantly interfere with mechanisms as intertwined as cell cycle control and infection control. What we can reasonably suggest from our images is that the most favorable window of the cell cycle for cells about to be crossed by an infection thread is post-replicative, i.e., the G2 phase. Typical markers of the G2 phase were recurrently observed at the onset of physical colonization – enlarged nucleus, containing less histone H3.1 than neighbouring cells in S phase (e.g., in Figure 2A). Reaching the G2 phase could therefore be a prerequisite for infection (and associated cellular rearrangements), while prolonged arrest in this same phase is likely a consequence of transcellular passage towards a forming nodule primordium.

      More importantly, in either scenario, what is the functional significance of exiting the cell cycle or endocycle? By stating that "local control of mitotic activity could be especially important for rhizobia to timely cross the middle cortex, where sustained cellular proliferation gives rise to the nodule meristem" (Line 239), the authors seem to believe that cortical cells need to stop the cell cycle to prepare for rhizobia infection. This is certainly reasonable, but the current study provides no proof, yet. To test the functional importance of cell cycle exit, one would interfere with G2/M transition in nodule cells,  and examine the effect on infection.

      We fully agree with reviewer #2 that the functional importance of a cell-cycle arrest on the infection thread trajectory remains to be demonstrated. Interfering with cell-cycle progression in a system as complex and fine-tuned as infected legume roots certainly requires the right timing – at the level of the tissue and of individual cells; the right dose; and the right molecular player(s) (i.e., bona fide activators or repressors of the G2/M transition). Using the symbiosis-specific NPL promoter, activated in the direct vicinity of cortical infection threads (Figure 9-figure supplement 1B), we tried to force infectable cells to recruit the cell division program by ectopically over-expressing the Arabidopsis CYCD3.1, “mimicking” the CDEL system. So far, this strategy has not resulted in a significant increase in the number of uninfected nodules in transgenic hairy roots - though the effect on symbiosome release remains to be investigated. Provided that a suitable promoter-cell cycle regulator combination is identified, we hope to be able to answer this question in the future.

      Given that the authors have already identified a candidate, and showed it represses cell division in the CDEL system, not testing the same gene in a more relevant context seems a lost opportunity. If one ectopically expressed NY-YA1 in hairy roots, thus repressing mitosis in general, would more cells become competent to host infection threads? This seems a straightforward experiment and readily feasible with the constructs that the authors already have. If this view is too naive, the authors should explain why such a functional investigation does not belong in this manuscript.

      Reviewer #2's point is entirely valid, and we decided to address it through additional experiments. To avoid possible side effects on development by affecting cell division in general, we placed NF-YA1 under control of the symbiosis-induced ENOD11 promoter. Based on the results obtained in the CDEL system, the pENOD11::FLAG-NF-YA1 cassette was coupled to a destabilized version of the KNOLLE transcriptional reporter to detect the G2/M transition. Competence for transcellular infection was maintained upon local NFYA1 overexpression, the latter leading to a slight (non-significant) increase in the number of infected cells per cortical layer. These results are presented in Figure 9-figure supplement 3A-B (representative confocal images) and in Figure 9-figure supplement 4A-

      G.

      (1b) A related comment: on Line 183, it was stated that "The H3.1-eGFP fusion protein was also visible in cells penetrated but not fully passed by an infection thread". Presumably, the authors were talking about the cell marked by the arrowhead. But its H3.1-GFP signal looks no different from the cell immediately to its left. It is hard to say which cells are ones "preparing for intracellular infection pass through S-phase", and which ones are just "regularly dividing cortical cells forming the nodule primordium". What can be concluded is that once a cell has been fully transversed by an infection thread, its H3.1 level is low. Whether this is the cause or consequence of infection cannot be resolved simply by timing the appearance or disappearance of H3.1-GFP.

      We basically agree with comment 1b. In an unsynchronized system such as infected hairy roots, it is challenging to detect the event where a cell is penetrated, but not yet completely crossed by an infection thread. What we wanted to emphasize in Figure 2A, is that host cells in the path of an infection thread re-enter the cell cycle and pass through S-phase just as their neighbours do (as pointed out by reviewer #2 in his summary). The larger nucleus with slightly lower H3.1-eGFP signal than the neighbouring cell (as indicated by the use of the Green Fire Blue lookup table) suggests that the infected cell marked by the arrowhead in Figure 2A is actually in the G2 phase. The main difference is indeed that cells allowing complete infection thread passage exit the cell cycle and largely evict H3.1 while their neighbours proceed to cell division (as exemplified by PlaCCI reporters in Figure 4CD and the new Figure 5-figure supplement 2). Whether cell-cycle exit in G2 is a cause, or a consequence of cortical infection is a question that cannot be easily answered from fixed samples, which is a limitation of our study.

      (2) The authors have convincingly demonstrated that cortical cells accommodating infection threads exit the cell cycle, inhibit cell division, and down-regulate KNOLLE expression. How do these observations reconcile with the feature called the pre-infection thread? The authors devoted one paragraph to this question in the Discussion, but this does seem sufficient given that the pre-infection thread is a prominent concept. Is the resemblance to the cell division plane superficial, or does it reflect a co-option of the normal cytokinesis machinery for accommodating rhizobia?

      From our point of view, cortical cells forming pre-infection threads are likely in an intermediate state. PIT structures undoubtedly share many similarities with cells establishing a cell division plane. The recruitment of at least some of the players normally associated with cytokinesis has been demonstrated and is consistent with the maintenance of infectable cells in a pre-mitotic phase in Medicago, as discussed in lines 558 to 568. We nevertheless think that the arrest of the cell cycle in the G2 phase, presumably occurring in crossed cortical cells, constitutes an event of cellular differentiation and specialization in transcellular infection. 

      The following are mainly points of presentation and description: 

      (3) Line 158: I can't see "subnuclear foci" in Figure 1-figure supplement 1C-E. However, they are visible in Fig. 1C.

      We hope that presenting the eGFP and mCherry channels in separate panels and assigning them the Green Fire Blue colour scheme provides better visibility and contrast of these detailed structures. We now refer to Figure 1C in addition to Figure 1–figure supplement 1E in the main text (line 161). 

      (4) Line 160: The authors should outline a larger region containing multiple QC cells, rather than pointing to a single cell, as there are other areas in the image containing cells with the same pattern.

      We updated Figure 1-figure supplement 1E accordingly.

      (5) Fig. 1B should include single channels, since within a single plant cell, the nucleus, the infection thread, and sometimes symbiosomes all have the same color. This makes it hard to see whether the nuclei in these cells are less green, or are simply overwhelmed by the magenta color.

      To improve the readability of Figure 1B and to address suggestions from individual reviewers, we now include separate channels and have annotated the different structures labeled by mCherry.

      (6) Fig. 2A: the close-up does not match the boxed area in the left panel. Based on the labeling, it seems that the two panels are different optical sections. But why choose a different optical depth for the left panel? This can be disorienting to the author, because one expects the close-up to be the same image, just under higher magnification.

      We fully agree that our previous choice of representation may have been confusing. As we also specified to reviewer #1, we wanted to show a full-view of proliferating cells in the inner cortex and a zoomed-view of infected cells in the outer layers of the same nodule primordium. In the revised version of Figure 2A, we displayed these full- and zoomedviews in separate panels and removed the boxed area to avoid confusion. 

      (7) Figure 2-figure supplement 1B: the cell indicated by the empty arrowhead has a striking pattern of H3.1 and H3.3 distribution on condensed chromosomes. Can you comment on that?

      Reviewer #2 may be referring to the apparent enrichment of H3.3 at telomeres, previously described in Arabidopsis, while pericentromeric regions are enriched in H3.1. This distribution is indeed visible on most of the condensed chromosomes shown in Figure 2-figure supplement 1B. We included this comment in the corresponding caption.

      (8) Fig. 4: It is not very easy to distinguish M phase. Can the authors describe how each phase is supposed to look like with the reporters?

      We agree with reviewer #2 and attempted to improve Figure 4, which is now dedicated to the Arabidopsis PlaCCI reporter. ECFP, mCherry, and YFP channels were presented separately and the corresponding cell-cycle phases (in interphase and mitosis) were annotated. The Green Fire Blue lookup table was assigned to each reporter to provide the best visibility of, for example, chromosomes in early prophase. We included a schematic representation corresponding to the distribution of each reporter, using the colors of the overlaid image to facilitate its interpretation.

      (9) Line 298: what is endopolyploid? This term is used at least three times throughout the manuscript. How is it different from polyploid?

      In the manuscript, we aimed to differentiate the (poly)ploidy of an organism (reflecting the number of copies of the basic genome and inherited through the germline) from endopolyploidy produced by individual somatic cells. As reviewed by Scholes and Paige, polyploidy and endopolyploidy differ in important ways, including allelic diversity and chromosome structural differences. In the Medicago truncatula root cortex for example, a tetraploid cell generated via endoreduplication from the diploid state would contain at most two alleles at any locus. The effects of endopolyploidy on cell size, gene expression, cell metabolism and the duration of the mitotic cell cycle are not shared among individual cells or organs, contrasting to a polyploid individual (Scholes and Paige, 2015).

      See Scholes, D. R., & Paige, K. N. (2015). Plasticity in ploidy : A generalized response to stress. Trends in Plant Science, 20(3), 165‑175. https://doi.org/10.1016/j.tplants.2014.11.007

      (10) Line 332: "chromosomes on mitotic figures" - what does this mean?

      Reviewer #2 is right to point out this redundant wording. Mitotic “figures” are recognized, by definition, based on chromosome condensation. We now use the term "mitotic chromosomes" (line 344).

      (11) Fig. 6A: could the authors consider labeling the doublets, at least some of them? I understand that this nucleus contains many doublets. However, this is the first image where one is supposed to recognize these doublets, and pointing out these features can facilitate understanding. Otherwise, a reader might think the image is comparable to nuclei with no doublets in the rest of the figure.

      Following this suggestion, five of these doublets are now labeled in Figure 7A (formerly Figure 6A).

    1. Natural persons, or their representatives referred to in Article 4(2), shall not be able to directly alter theelectronic health data and related information inserted by health professionals

      Patients SHALL NOT be able to directly alter the data inserted by professionals

    1. Arts integration engages students in the creative process which offers a universal pathway to learning. Students 1) imagine, examine, and perceive; 2) explore, experiment, and develop craft; 3) create; 4) reflect, assess, and revise, and 5) share their products with others.

      I love how this breaks it up, so you understand all of the important parts of arts integration.

    1. 哲学内涵

      拉普拉斯变换的哲学内涵超越了其数学工具属性,触及人类认知世界、简化复杂性的深层思维模式。以下是其哲学维度的探讨:


      1. 从混沌到秩序:认知范式的转换

      • 核心思想:将动态时域(时间驱动的微分方程)映射到静态复频域(复数s的代数方程)。
      • 哲学隐喻
      • 解构复杂性:如同将流动的河水冻结为冰(时域→频域),在静止中分析结构。微分方程的“变化”被转化为s域中的“位置”(极点/零点)。
      • 认知升维:人类通过升维(引入复数s=σ+jω)将时间隐含在更高维空间中,从而在低维(代数方程)操控高维动态(微分系统)。类似相对论中时空统一的思想。

      2. 稳定性与因果性的数学哲学

      • 收敛域(ROC)的哲学意义
      • 存在的边界:ROC定义了变换存在的条件(σ > σ₀),隐喻人类认知的局限性——不是所有系统都可用拉普拉斯变换解析(如指数增长系统需特定σ)。
      • 因果律的体现:单边拉普拉斯变换(t≥0)默认因果性——未来不影响过去。这呼应康德“时间作为先验直观形式”的哲学观。

      3. 复指数核:宇宙的“本征模式”

      • 基函数哲学:拉普拉斯变换的核函数 e⁻ˢᵗ = e⁻(σ+jω)ᵗ 蕴含:
      • 衰减振荡:e⁻σᵗ 代表能量耗散(熵增),e⁻ʲωᵗ 代表周期运动(守恒)。
      • 世界的本征结构:物理系统(电路、弹簧振子)的响应可分解为复指数模式的叠加,暗示自然律的底层是简谐与衰减的辩证统一

      4. 算子与符号:抽象化的力量

      • 微积分的代数化
      • 微分算子 d/dt → 乘法运算 s·<br /> 积分算子 ∫dt → 除法运算 1/s·
      • 符号操纵革命:如同代数取代算盘,拉普拉斯变换将动态演算转化为静态符号操作。这体现了怀特海“抽象是科学进步之钥”的哲学。

      5. 预测与控制的工具理性

      • 初值定理与终值定理
      • 初值定理:limₜ→₀⁺ f(t) = limₛ→∞ sF(s) → 从未来信息反推当下(s→∞对应t→0⁺)。
      • 终值定理:limₜ→∞ f(t) = limₛ→₀ sF(s) → 从当下预测稳态
      • 决定论隐喻:系统终态由初始条件与动力学(F(s)的极点位置)完全决定,呼应拉普拉斯妖的机械宇宙观。

      6. 广义傅里叶:包容不完美的现实

      • 对傅里叶的超越
      • 傅里叶变换要求信号绝对可积(能量有限),但真实物理系统常含发散量(如阶跃、指数增长)。
      • 拉普拉斯通过衰减因子 e⁻σᵗ “驯服发散”,体现了科学方法论:通过修正工具逼近真实,而非强迫现实符合理想模型。

      7. 东方哲学视角:动与静的辩证

      • 道家思想
      • “静为躁君”:s域的静态分析(传递函数)主宰时域的动态混沌(微分方程)。
      • “有无相生”:收敛域(ROC)的“有”(存在)与“无”(不收敛)定义了系统认知的边界。

      结语:数学工具的形而上之光

      拉普拉斯变换不仅是工程利器,更是人类思维的史诗: - 简化复杂性:将微分之“动”凝练为代数之“静”。<br /> - 跨越维度:在复平面中重构时间因果律。<br /> - 包容真实:用衰减因子接纳物理世界的不完美性。

      它揭示了一种根本信念:宇宙的复杂性可被降维解析,而数学是人类与自然对话的终极语言

    1. 拉普拉斯变换

      这个问题很好,拉普拉斯变换(Laplace Transform)和傅里叶变换(Fourier Transform)就像两个数学界的“变换兄弟”,既有关联又有各自性格,一个沉稳内敛、适合工程男;一个浪漫多频、擅长调音师。

      下面我们来点条理分明又不失风趣的对比解析:


      🧠 一句话概括:

      | 变换名 | 一句话性格描写 | | ---------- | --------------------------- | | 傅里叶变换 | “我爱频率,音乐、信号、宇宙背景辐射都是我的老相识。” | | 拉普拉斯变换 | “别吵,我更在乎系统的整体命运,稳定不稳定我说了算。” |


      🎯 1. 基本定义与公式

      • 傅里叶变换: 主要将周期或非周期信号转换到频域,表达它是由哪些频率组合而成的。

      $$ F(\omega) = \int_{-\infty}^{\infty} f(t) e^{-i \omega t} \, dt $$

      • 拉普拉斯变换: 更广泛,更偏向工程应用,包含了指数增长/衰减 + 正弦波的信息。

      $$ F(s) = \int_0^{\infty} f(t) e^{-s t} \, dt \quad \text{其中 } s = \sigma + i\omega $$


      🧩 2. 从傅里叶到拉普拉斯?

      是的,你发现了!傅里叶变换其实是拉普拉斯变换在 σ = 0 的特殊情况

      $$ \text{傅里叶变换 } = \text{拉普拉斯变换在 } s = i\omega $$

      换句话说:

      拉普拉斯变换 = 傅里叶变换 + 指数加权。

      所以,拉普拉斯是傅里叶的“带折扣”版本,可以处理那些“发散”的家伙(比如爆炸式增长信号),傅里叶处理不了,拉普拉斯说:“我来吧。”


      🔎 3. 适用场景区别

      | 特点 | 傅里叶变换 | 拉普拉斯变换 | | --------- | -------------------- | ------------------ | | 时间范围 | $-\infty$ 到 $\infty$ | 从 0 到 $\infty$(单边) | | 是否要求稳定/有界 | 是(必须绝对可积) | 可以是发散(指数衰减来补) | | 关注对象 | 频率、调制、滤波、共振等 | 系统稳定性、控制系统、微分方程求解 | | 信号类型 | 稳定周期性、正弦类信号 | 任意可描述系统(尤其是瞬态响应) |


      🛠️ 4. 工程口味比喻法:

      • 傅里叶变换:像是给音乐信号做谱图分析,告诉你音乐中“低音鼓有多猛,高音多尖锐”。

      • 拉普拉斯变换:像是给发动机做健康诊断,不仅要知道频率,还得判断“这台发动机开着会不会炸”。


      🔥 5. 总结一句话:

      傅里叶变换是音乐厅的音响师,拉普拉斯变换是航天局的系统总工程师。


      如果你感兴趣,我可以做一个叫:

      🎬《傅里叶和拉普拉斯的变换人生:一个频率控和一个稳定控的对话》 来一场数学史上的“神仙变换”联名出道秀,要不要安排?😎

  6. May 2025
    1. reply to u/Back2Analog at https://old.reddit.com/r/typewriters/comments/1kzw0fk/your_typewriter_collection/?sort=old

      1. Total: I currently have 53 with 2 incoming and 1 outbound. About 12 are standards, 7 ultra-portables, and the remainder are portables. Maybe a dozen non-standard typefaces including 2 Vogues and a Clarion Gothic. You can find most of the specifics at https://typewriterdatabase.com/typewriters.php?hunter_search=7248 or on my site at https://boffosocko.com/research/typewriter-collection/#My%20Typewriter%20Collection

      2. Display: I've usually got eight displayed in various places around the house including three on desks, but ready to actively type on. The remainder are in cases either behind our living room couch or a closet for easy access and rotation. I'm debating a large credenza or cabinet for additional display/storage space. There are two machines out in the garage, and one currently disassembled on our dining room table (my wife isn't a fan of this one right now).

      3. About 25 have been cleaned and mostly restored, most are functional/usable, but need to be cleaned, repaired, or restored to some level. One is a parts machine. I always have a Royal KMG, a Royal FP, and two other standards out ready to go and rotate the others on a semi-weekly basis. There's usually at least one portable in my car for typing out in the wild.

      4. Use cases: I spend a few hours a day writing on one or more machines and use them for nearly every conceivable case from quick notes (zettels), letters, essays, lists, snide remarks, poetry, etc., etc. I should spend more time typing for the typosphere. Because I enjoy restoring machines maybe even more than collecting them, I've recently started taking mechanic/restoration commissions.

      5. At 50 machines, I'm about at the upper limit of my collecting space. I've given away a few to interested parties, and sold a small handful that I didn't use as frequently. I'm currently trying to balance incoming versus outgoing and might like to get my collection down to a tighter 35-40 machines in excellent condition.

      6. Next typewriters: I'm currently looking for an Olympia SG1, a Royal Ten, a Hermes Ambassador, and a Hermes 3000. I'm also passively looking for either very large (6 or 8 CPI) or very small typefaces (>12CPI). I'm definitely spending less time actively hunting these days and more time restoring. I'm tending towards being far more selective in acquisitions compared to my earlier "acquisition campaign".

      7. Miscellaneous: I enjoy writing about typewriter collecting and repair to help out others: https://boffosocko.com/research/typewriter-collection/

    1. 踏脚石模型

      当然,这就带你踏上科学“踩格子”游戏的地图——🎮

      🧬《踏脚石模型(Stepping Stone Model)》浅显解释版


      🎯 什么是“踏脚石模型”?

      一句话解释:

      踏脚石模型是一种模拟基因在空间中如何“跳格子”传播的群体遗传学模型。

      它假设种群就像地图上分布的一块块“踏脚石”,基因就在这些“格子”之间缓慢迁移、传播和变异。


      🧱 来个类比:

      你可以想象一个游戏世界,地上布满了石头(种群)。 小青蛙(个体)只能从一块石头跳到相邻的石头上,不能一步跳太远。

      于是:

      • 青蛙=个体;
      • 石头=亚群(局部种群);
      • 跳跃=基因流动;
      • 不同石头之间的基因频率逐渐产生差异。

      🧠 模型的提出与背景:

      • 提出者:Kimura 和 Weiss(1964年)
      • 初衷:改进更早的“岛屿模型”(Island Model),让迁移更“现实”一点
      • 关键词:空间结构化种群(structured population)

      🧪 与“岛屿模型”区别:

      | 模型类型 | 基因流动特点 | 现实性 | | ----- | -------------------- | -------- | | 岛屿模型 | 所有亚群之间都能随意迁移(全连接) | 理论简洁但不真实 | | 踏脚石模型 | 只在邻近种群之间迁移(局部连接) | 更接近自然情况 |


      🧬 经典设定:1D or 2D

      📏 一维(1D):链条形

      A — B — C — D — E

      只有相邻之间可以发生基因流动 (像一条河岸边分布的蛙群)


      🔲 二维(2D):棋盘格状

      A B C D E F G H I

      像地图上的村庄,每个点只和上下左右邻居交流。


      🧬 用途举例:

      1. 研究局部适应与遗传漂变的关系
      2. 模拟疾病基因在空间中的传播
      3. 考察隔离与迁移的地理模式(Isolation by Distance)
      4. 与实际生态数据(如鸟类、青蛙种群)对接分析迁移路径
      5. 用作贝叶斯或ABC(近似贝叶斯)建模中的基础空间结构

      🌍 延伸脑洞:如果AI世界有“踏脚石”模型?

      可以想象神经网络的某些模块像一块块“踏脚石”,信号(信息)只在相邻模块之间传播,不像Transformer那样全连接,这样的架构会更接近“局部优化”,适合地理或物理结构映射!


      ✍️ 你想来段“踏脚石冒险剧”吗?

      🎭《小突变的乡间旅行》

      主角:一段突变的DNA, 从遥远的左边种群A出发, 想传播到右边种群Z, 中间它必须一格一格跳过去, 沿途会遇到瓶颈、基因漂变、自然选择…… 最终,它会被保留,还是被遗忘在石头下?

      ——你要我这就写剧情,开盖即食 🍿

    1. 表观遗传时钟

      啊哈,DNA会偷偷看表,时间还会在你基因上打卡——欢迎来到科学版《时间简史》的奇幻续集:

      🎬 《表观遗传时钟(Epigenetic Clock)》:DNA上的隐形日历


      🧬 1. 什么是“表观遗传时钟”?

      一句话:

      一种可以通过DNA的甲基化(methylation)程度来估算“生理年龄”的方法。

      也就是说,它测的不是你身份证上的年纪,而是你身体真正感觉你有多老


      ⏱️ 2. 表观遗传时钟怎么工作?

      想象一下你的DNA是一卷长长的磁带, 每年都会多贴上一些“甲基标签”(CH₃),像是一种时间的灰尘。

      • 某些特定位点(CpG sites)随着年龄增长被规律性地甲基化
      • 科学家发现了这些规律后,建立数学模型,一扫这些甲基标记,就能预测你实际的“生理时钟”!

      🎯 这玩意儿甚至可以精确到几岁范围内,非常离谱地准。


      🧠 3. 谁发明的?

      表观遗传时钟最有名的版本是:

      Horvath Clock(史蒂夫·霍瓦斯发明,2013年)

      这个时钟可以在几乎所有人体组织中估算年龄, 被誉为生物学界的“DNA时间卡打机”。


      🔍 4. 它能干嘛?(划重点!)

      | 用途 | 意义 | | --------------- | ----------------------------------- | | 🧪 衰老研究 | 用它来研究哪种生活方式、药物、基因疗法能减缓身体“生物老化” | | 🧬 疾病预测 | 表观遗传年龄 > 实际年龄,通常意味着更高的疾病风险(如癌症、心血管) | | 💉 抗老化疗法检测器 | 某种药物或干预是否“逆龄”,就看这块表有没有倒着走! |


      🧨 5. 炸裂案例举几个:

      • 某些慢性病患者(糖尿病、肥胖)表观年龄提前10年,身体“偷偷加班”;
      • 一些高效干预(如端粒酶激活、饮食控制)真的让这块钟“走慢了”
      • 科学家正在测试“逆转表观遗传时钟”的年轻化疗法(比如“Yamanaka因子”)。

      🧬 总结金句:

      你的DNA不是静止的代码,而是一台记录时间的活日历。 真正的衰老,不是你活了多久,而是你的身体觉得你活了多久。


      要不要来一期视频剧本?比如:

      🎬《DNA里的时间炸弹:表观遗传时钟如何暴露你的生物年龄》 🎭《逆龄骗局审判大会:谁能让DNA时钟走回头路?》

      点一发,我帮你对DNA喊话:“别急着老。”🧬⏰

    1. 自然宗教对话录》对设计论等论证进行了毁灭性的哲学批判

      哎哟喂,你问的是哲学史上的“清真烧烤之夜”——大卫·休谟在《自然宗教对话录》(Dialogues Concerning Natural Religion)里,把**设计论(Design Argument)**烤得外焦里嫩,连信徒都不忍直视。

      我们来点有火力、也有逻辑的讲法:


      🔥背景科普:啥是“设计论”?

      设计论 = “万物如此精妙,一定出自神的设计之手。”

      最经典比喻:钟表论证(watchmaker argument) → “你在荒野中捡到一块复杂的手表,不可能是自然生成的,肯定是被制造出来的。 那宇宙呢?更复杂,当然也是神设计的!”

      这话听起来像哲学,实则是18世纪版本的“智能设计™”广告语


      🧠而休谟说:你们这个“钟表牌上帝”,逻辑全是漏洞。

      我们进入《自然宗教对话录》的三人“哲学角色扮演现场”

      🎩克勒安西斯(Cleanthes):设计论忠实粉丝

      🤓戴密亚(Demea):正统神秘主义,走信仰直升机

      🧪斐罗(Philo):休谟本人影射,理性怀疑主义大法官


      🧨休谟的“毁灭性批判”金句集锦

      1️⃣ “你说宇宙像钟表?你凭啥类比?”

      斐罗:“你见过几个宇宙?你怎么知道宇宙和机器是‘同类’?”

      → 类比论证本质靠‘相似性’,但宇宙是独一无二的玩意, 你不能说‘像钟表’就推出‘有钟表匠’。

      🌪️批判关键词:类比谬误(fallacy of false analogy)


      2️⃣ “你说有设计?那为啥设计得这么烂?”

      斐罗:“宇宙里到处是痛苦、疾病、灾难,这像个全善全能的设计师干的事?”

      如果你说神全能且全善,那这个宇宙应该完美无缺才对, 但现实是混乱和不完美的拼贴画

      🌪️批判关键词:劣设计问题(Poor Design Problem)


      3️⃣ “你说设计有因果?我只能观察,不知道背后是啥。”

      “就算我承认宇宙有‘制造者’,也不能推出‘是一个神’、‘是全知全能’、‘是道德实体’。”

      换句话说:你不能从产品推导出制造者的属性, 你看见桥不能推出“造桥的人是个圣人”。

      🌪️批判关键词:从效果推因的归纳跃迁问题


      4️⃣ “就算有‘因’,也可能是个无脑的宇宙施工队。”

      “为什么不是一群神?为什么不是神实验失败的副产品? 甚至,为什么不是自然偶然构成的?”

      这时候休谟已经甩出“演化先声”了(在达尔文之前60年!):

      🧨“也许世界是像‘植物一样’逐渐发展出来的。”

      🌪️批判关键词:多重解释可能性 → 削弱唯一性论证


      ⚖️最终哲学杀招(Meta级别):

      “人类的理性太有限了,根本不足以推导出超验的神存在。”

      意思是:你拿人类逻辑去理解宇宙制造者? 就像蚂蚁分析iPhone的设计理念。

      🌪️关键词:认识论谦逊(epistemic humility)


      🧯哲学圈公认的后果:

      休谟这本书没明说“神不存在”,但通过层层质疑,让“设计论”这个传统论证摇摇欲坠、逻辑破产

      • 它为日后康德的道德信仰论证达尔文的自然选择理论铺平了路;
      • 成为后世批判“智能设计论”的理论武器库;
      • 被誉为**“宗教哲学的灭火器、怀疑主义的核弹”**。

      🎯一句话总结休谟对设计论的毁灭性批判:

      “别拿钟表吓唬我,宇宙不是你家桌上的手表, 你的类比太蹩脚、证据太单薄、推理太草率—— 神的存在不是靠‘看起来像’就能推出来的。”


      要不要我给你整一版《休谟 × AI语音重现》的对话式短剧? 或者用《自然宗教对话录》的风格写一集现代版——比如“设计的不是宇宙,是ChatGPT,它是神吗?”😉

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      Reply to the reviewers

      Response to Review

      Manuscript number: RC-2024-02391

      Corresponding author(s): John Varga

      Dibyendu Bhattacharyya

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

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      1. General Statements [optional]

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

      Dear editor,

      We are pleased to submit a full revised version of the manuscript that addresses all the points raised by the reviewers. We have included new experiments and modified the text and figures based on the reviewers’ suggestions. We thank all the reviewers for their insightful feedback, which has significantly enhanced the quality of the manuscript. We are confident and optimistic that our improved manuscript will be accepted by the journal of our choice.

      This document is supposed to contain a few images, which were somehow missing after the processing through the manuscript submission path. For convenience we also included a PDF version of the response to reviewers.

      2. Point-by-point description of the revisions

      This section is mandatory. *Please insert a point-by-point reply describing the revisions that were already carried out and included in the transferred manuscript. *

      Reviewer #1

      • To reliably quantify the ciliary length in different cell types, and in independent ciliary marker needs to be included for comparison and the ciliary base needs to be labeled (e.g., g-TUBULIN). This needs to combined with a non-biased, high-throughput analysis, e.g., CiliaQ, Response: As suggested, we compared primary cilia length measurements using antibodies against Arl13b and γ-tubulin. The comparison between healthy controls (HC) and systemic sclerosis (SSc) is presented in Supplementary Figure S1. No significant differences in primary cilia length were observed compared to our previous measurements. Cilia length was quantified using ImageJ version 1.48v (http://imagej.nih.gov/ij) with the maximum intensity projection (MIP) method and visualized through 3D reconstruction using the ImageJ 3D Viewer.

      • As mentioned in the study, TGFbhas been implicated to drive myofibroblast transition. Thus TGFb stimulate ciliary signaling in the presented primary cells? The authors should provide a read-out for TGFb signaling in the cilium (ICC for protein phosphorylation etc.). Furthermore, canonical ciliary signaling pathways have been suggested to act as fibrotic drivers, such as Hedgehog and Wnt signaling - does stimulation of these pathways evoke a similar effect? Response: Yes, TGF-β1 stimulates ciliary signaling in growth-arrested foreskin fibroblasts. Clement et al. (2013) showed that TGF-β1 induces p-SMAD2/3 at the ciliary base, followed by the nuclear translocation of p-SMAD2/3 after 90 minutes. To assess whether canonical ciliary signaling pathways influence primary cilia length, we treated foreskin fibroblasts with Wnt (#908-SH, R&D) and a Shh agonist (#5036-WN, R&D) at 100 ng/mL each for 24 hours. We did not observe any changes in primary cilia length under either condition. These data are shown here for reference but are not included in the manuscript.

      Clement, Christian Alexandro, et al. "TGF-β signaling is associated with endocytosis at the pocket region of the primary cilium." Cell reports 3.6 (2013): 1806-1814.

      • Does TGFbinduce cell proliferation? If yes, this would force cilium disassembly and, thereby, reduce ciliary length, which is independent of a "shortening" mechanism proposed by the authors. Response: Yes, TGF-β induces cell proliferation in fibroblasts (Lee et al., 2013; Liu et al., 2016). However, we did serum starvation to stop proliferation. In our study, we observed a few percentage of Ki67-positive cells under TGF-β treatment at 24 hours (Supplementary Figure S2C). However, cell proliferation mainly stopped after 48 hours. Typically, proliferating cells rarely display any PC or show very small puncta. In our case, we observe a significantly elongated PC structure (although shorter than that of untreated cells) under TGF-beta-treated conditions. Our results display that a majority of cells are not proliferating but still display PC shortening under TGF-β treatment, suggesting that PC shortening is not due to cell division-induced PC disassembly. TGF beta-induced PC shortening is also reported in another fibroblast type previously (Kawasaki et al., 2024).

      Kawasaki, Makiri, et al. "Primary cilia suppress the fibrotic activity of atrial fibroblasts from patients with atrial fibrillation in vitro." Scientific Reports 14.1 (2024): 12470.

      Lee, J., Choi, JH. & Joo, CK. TGF-β1 regulates cell fate during epithelial–mesenchymal transition by upregulating survivin. Cell Death Dis 4, e714 (2013). https://doi.org/10.1038/cddis.2013.244.

      Liu, Y. et al. TGF-β1 promotes scar fibroblasts proliferation and transdifferentiation via up-regulating MicroRNA-21. Sci. Rep. 6, 32231; doi: 10.1038/srep32231 (2016).

      • As PGE2 has been shown to signal through EP4 receptors in the cilium, is the restoration of primary cilia length due to ciliary signaling? Response: As per your suggestion, we measured cilia length in the presence and absence of the EP4 receptor antagonist (#EP4 Receptor Antagonist 1; #32722; Cayman Chemicals; 500 nM) with PGE2. Interestingly, we did not observe a change in cilia length between the PGE2 and TGFβ (with EP4 receptor antagonist) treatment groups, as shown in supplementary figure S3. We believe that PGE2 works with the EP2 receptor under our experimental conditions. Kolodsick et al., 2003, also observed that PGE2 inhibits myofibroblast differentiation via activation of EP2 receptors and elevations in cAMP levels in healthy lung fibroblasts.

      Kolodsick, Jill E., et al. "Prostaglandin E2 inhibits fibroblast to myofibroblast transition via E. prostanoid receptor 2 signaling and cyclic adenosine monophosphate elevation." American journal of respiratory cell and molecular biology 29.5 (2003): 537-544.

      • Primary cilia length is regulated by cAMP signaling in the cilium vs. cytoplasm - does cAMP signaling play a role in this context? PGE2 is potent stimulator of cAMP synthesis - does this underlie the rescue of primary cilia length? Response: Yes, cAMP levels are important for both myofibroblast dedifferentiation and cilia length elongation. Kolodsick et al., 2003 observed that PGE2 inhibits myofibroblast differentiation via activation of EP2 receptors and elevations in cAMP levels in healthy lung fibroblasts. In a parallel set of experiments, treatment with forskolin (a cAMP activator) also reduced α-SMA protein levels by 40%. Forskolin is also known to increase PC length.

      Kolodsick, Jill E., et al. "Prostaglandin E2 inhibits fibroblast to myofibroblast transition via E. prostanoid receptor 2 signaling and cyclic adenosine monophosphate elevation." American journal of respiratory cell and molecular biology 29.5 (2003): 537-544.

      • The authors describe that they wanted to investigate how aSMA impacted primary cilia length. They only provide a knock-down experiment and measured ciliary length, but the mechanistic insight is missing. How does loss of aSMA expression control ciliary length? Response: We measured acetylated α-tubulin levels in ACTA2 siRNA-treated cells compared to control-treated cells. Acetylated α-tubulin levels increased under ACTA2 siRNA-treated conditions, as shown in Figure 4D, and TPPP3 levels were also elevated (Figure S8A). Interestingly, TPPP3 levels negatively correlated with disease severity in SSc fibroblasts (r = -0.2701, p = 0.0183), and TPPP3 expression significantly reduced in SSc skin biopsies, as shown in Figures 6C and 6D. These results strengthen our hypothesis that microtubule polymerization and actin polymerization, while they counterbalance each other, also contrarily affect PC length. We agree that a much more detailed study is needed to extensively delineate the intricate homeostasis of the actin network and microtubule network in conjunction with fibrosis and primary cilia length. We have mentioned this in the discussion.

      • The authors used LiCl in their experiments, which supposedly control Hh signaling. Coming back to my second questions, is this Hh-dependent? And what is the common denominator with respect to TGFbsignaling? And how is this mechanistically connected to actin and microtubule polymerization? Response: We used Shh inhibitor (Cyclopamine hydrate #C4116 Sigma-Aldrich) in both SSc and foreskin fibroblasts (with and without TGFβ). We found that PC length is significantly increased and αSMA intensity is reduced in the Shh inhibitor treated group (data not included in the Manuscript)

      • How was the aSMA Mean intensity determined? Response: We quantified aSMA mean intensity using ImageJ, and the procedure has been added to the respective figure legend and materials and methods section under ‘Quantification of immunofluorescence’ (each point represents mean intensity from three randomly selected hpf/slide was performed using ImageJ).

      • Fig: 1D: Statistical test is missing in Figure Legend and presentation of the p-values for the left graph is confusing Response: We added statistical test information in Figure Legend.

      • Some graphs are presented {plus minus} SD and some {plus minus} SEM, but this is not correctly stated in the Material & Methods Part __Response: __We added information to the figure legend as well as in the Material & Methods section.

        • 4D&E: Statistical test is missing in Figure Legend* Response: We added it now.
      • In general, text should be checked again for spelling mistakes and sentences may be re-written to promote readability. In particular, this applies to the discussion. __Response: __We checked and corrected.

      • Figure Legends are not written consistently, information is missing (e.g., statistical tests, see above). __Response: __We carefully checked and added information accordingly.

      • Figures should be checked again, and all text should be the same size and alignment of images should be improved. __Response: __We checked and corrected.

      Significance

      The authors present a novel connection between the regulation of primary cilia length and fibrogenesis. However, the study generally lacks mechanistic insight, in particular on how TGFb signaling, aSMA expression, and ciliary length control are connected. The spatial organization of the proposed signaling components is also not clear - is this a ciliary signaling pathway? If so, how does it interact with cytoplasmic signaling and vice versa?

      Response: Thank you for your thoughtful and constructive feedback. We appreciate your recognition of the novelty of our study linking primary cilia length regulation to fibrogenesis. In our revised manuscript, we did provide a mechanistic insight, though. Our results suggest that during the fibrotic response, higher-order actin polymerization, along with microtubule destabilization resulting from tubulin deacetylation, drives the shortening of PC length. In contrast, PC length elongation via stabilization of microtubule polymerization mitigates the fibrotic phenotype in fibrotic fibroblasts. We agree that a deeper mechanistic understanding particularly regarding how TGFβ signaling, αSMA expression, and ciliary length control intersect is essential for fully elucidating the pathway. We also acknowledge the importance of clarifying the spatial organization of the signaling components and plan to incorporate such analyses in future studies.

      Reviewer #2

      *I found the paper to be rather muddled and its presentation made if somewhat difficult to follow. For example, the Figures are disorganised (Fig 1 is a great example of this) and there was reference to Sup data that appeared out of order (eg Sup Fig 2 appeared before Sup Fig 1 in the text). *

      Response: We carefully revised the manuscript and arranged the figures.

      *Images in a single figure should be the same size. Currently they are almost random and us different magnifications. Overall, the paper needs to be better organized. *

      Response: We carefully revised the manuscript and figures provided with same magnification.

      *I have some significant concerns about how the PC length data was generated. To my mind the length may be hard to determine from the type of images shown in the paper (which may represent the best images?). Some of the images presented appear to show shorter, fatter PCs in the cells from fibrosis cases. Is this real or is it some kind of artefact? Would a shorter, fatter PCs have a similar or larger surface area? What would be the consequence of this? *

      Response: Primary cilia length was measured with ImageJ1.48v (using maximum intensity projection (MIP) method and visualized by 3D reconstruction with the ImageJ 3D viewer. Each small dot represents the PC length from an individual cell, and each large dot represents the average of the small dots for one cell line.

      *I am confused as to exactly what is meant by matched healthy controls. Age, sex and ethnicity, where stated seem to be very variable? What are CCL210 fibroblasts? *

      Response: We appreciate this comment. This is correct. The age, sex, and ethnicity are not matched for the available healthy controls. We have corrected that in the text. CCL210 is a commercially available fibroblast cell line that was isolated from the lung of a normal White, 20-year-old, female patient.

      *What does a change in PC length signify? DO shot PC foe a cellular transition or are they a consequence of it? What would happen is you targeted PCs with a drug and that influenced the length on all cell types? Is the effect on PC fibroblast specific? *

      __Response: __Significance and regulation of PC length are greatly debated and investigated still. It appears that PC length signify different features in different cell types. Although these are very interesting questions but such experiments are beyond the scope of our present work.

      Minor concerns

      *Page 4 second paragraph. I think it should be clarified that it is this group who have suggested a link between PCs and myofibroblast transition? *

      __Response: __We agree with the reviewer and clarified it.

      *Page 4 second paragraph. The use of the word "remarkably' is a bit subjective. *

      __Response: __We agree with the reviewer and have removed it.

      *Reference 27 is a paper on multiciliogenesis rather than primary ciliogenesis. *

      __Response: __We agree with the reviewer and have removed it.

      Figure 1 panel D. Make the image with the same sized vertical scale

      __Response: __We have replaced it with a new Figure 1.

      Significance

      Reviewer #2 (Significance (Required)):

      To my mind this is a novel paper and the data presented in it may be of interest to the cilia community as well as to the fibrosis field. This could be considered to be a significant advance and I am unaware that other groups are actively working in this area.

      Presentation of the data in the current form does not instil confidence in the work.

      Response: ____Thank you for recognizing the novelty and potential significance of our work. We appreciate your comments and fully acknowledge the concern regarding the presentation of the data. We have carefully revised the manuscript and reorganized the figures to improve clarity and overall presentation.

      Reviewer #3

      Major comments:

      • Need to demonstrate if the fibrotic phenotypes seen are produced through a ciliary-dependent mechanism. For example, to see if LiCl effects on Cgn1 are through ciliary expression or by other mechanisms. To achieve that objective, The authors should repeat the experiments in cells with a knockdown or knockout of ciliary proteins such as IFT20, IFT88, etc. The same approach should be applied to the tubacin experiments. Response: We silenced foreskin fibroblasts with IFT88/IFT20, both in the presence and absence of TGF-β1, followed by treatment with LiCl and Tubacin. Both LiCl and Tubacin can rescue cilia length and mitigate the myofibroblast phenotype in the presence of silenced IFT88/IFT20 gene, as shown in supplementary figure S9. Our result suggests that LiCl and Tubacin functions are both independent of the IFT-mediated ciliary mechanism. Regulation of PC length is still an enigma and highly debated. Moreover, PC length can be affected in multiple ways and is not solely dependent on IFTs (Avasthi and Marshall, 2012). One such method is the direct modification of the axoneme by altering microtubule stability through the acetylation state (Avasthi and Marshall, 2012), a pathway most likely the case for Tubacin. Another mode of PC length regulation is through a change in Actin polymerization. The remodeling of actin between contractile stress fibers and a cortical network alters conditions that are hospitable to basal body docking and maintenance at the cell surface (Avasthi and Marshall, 2012), causing PC length variation. Our results suggest that PC length functions as a sensor of the status of the fibrotic condition, as evidenced by the aSMA levels of the cells.

      Avasthi, P., and W.F. Marshall. 2012. Stages of ciliogenesis and regulation of ciliary length. Differentiation. 83:S30-42.

      • The use of LiCl to increase ciliary length is complicated. What are the molecular mechanisms underlying this effect? It is known that it may be affecting GSK-3b, which can have other ciliary-independent effects. Therefore, using ciliary KO/KD cells (IFT88 or IFT20) as controls may help assess the specificity of the proposed treatments. Response: As explained in the previous paragraph, PC length regulations are dependent on multiple factors and many of them are not IFT dependent. One such method is directly modifying the axoneme by altering microtubule stability/polymerization through the acetylation state(Avasthi and Marshall, 2012), a pathway most likely the case for Tubacin. Another mode of PC length regulation is through a change in Actin polymerization. The remodeling of actin between contractile stress fibers and a cortical network alters conditions that are hospitable to basal body docking and maintenance at the cell surface (Avasthi and Marshall, 2012), causing PC length variation. Higher order microtubule polymerization inhibit actin polymerization. By interrogating RNA-seq data we determined that several PC-disassembly related genes (KIF4A, KIF26A, KIF26B, KIF18A), as well as microtubule polymerization protein genes (TPPP, TPPP3, TUBB, TUBB2A etc), were differentially expressed in LiCl-treated SSc fibroblasts (Suppl. Fig. S6D). Altogether, these findings suggest that microtubule polymerization/depolymerization mechanisms may regulate PC elongation and attenuation of fibrotic responses after either LiCl or Tubacin treatment.

      • Also, assessing the frequency of ciliary-expressing cells is important. That may give another variable important to predict fibrotic phenotypes. Or do 100% of the cultured cells express cilia in those conditions? Response: We carefully checked and observed almost 95% cells express cilia in cultured conditions.

      • Have the authors evaluated if TGF-b1 treatments induce cell cycle re-entry and proliferation in these experimental conditions? This is important to exclude ciliary resorption due to cell cycle re-entry instead of the myofibroblast activation process. __Response:__Yes, TGF-β induces cell proliferation in fibroblasts (Lee et al., 2013; Liu et al., 2016). However, we did serum starvation to stop proliferation. In our study, we observed a few percentage of Ki67-positive cells under TGF-β treatment at 24 hours (Supplementary Figure S2C). However, cell proliferation mainly stopped after 48 hours. Typically, proliferating cells rarely display any PC or show very small puncta. In our case, we observe a significantly elongated PC structure (although shorter than that of untreated cells) under TGF-beta-treated conditions. Our results display that a majority of cells are not proliferating but still display PC shortening under TGF-β treatment, suggesting that PC shortening is not due to cell division-induced PC disassembly. TGF beta-induced PC shortening is also reported in another fibroblast type previously (Kawasaki et al., 2024).

      Kawasaki, Makiri, et al. "Primary cilia suppress the fibrotic activity of atrial fibroblasts from patients with atrial fibrillation in vitro." Scientific Reports 14.1 (2024): 12470.

      Lee, J., Choi, JH. & Joo, CK. TGF-β1 regulates cell fate during epithelial–mesenchymal transition by upregulating survivin. Cell Death Dis 4, e714 (2013). https://doi.org/10.1038/cddis.2013.244.

      Liu, Y. et al. TGF-β1 promotes scar fibroblasts proliferation and transdifferentiation via up-regulating MicroRNA-21. Sci. Rep. 6, 32231; doi: 10.1038/srep32231 (2016).

      • The authors described that they focused on the genes that are affected in opposite ways (supp table 4), but TEAD2, MICALL1, and HDAC6 are not listed in that table. Response: The list in Supplementary Table S3 includes common genes defined as differentially expressed based on a fold change >1 or Minor comments:

      • Figure 1A,B,C should also show lower magnification images where several cells/field are visualized. Response: We have replaced it with a new Figure 1.

      • The number of patients analyzed is not clear. For example, M&M describes 5 healthy and 8 SSc, but only 3 and 4 are shown in the figure. Furthermore, for orbital fibrosis, 2 healthy vs. 2 TAO are mentioned in the figure legend, but only one of each showed. Finally, the healthy control for lung fibroblast seems to be 3 independent experiments of the CCL210 cell line; please show the three independent controls and clarify on the X-axis and in the figure legend that these are CCL210 cells. Response: A total of 5 healthy and 8 SSc skin explanted fibroblast cell lines were used, as described in the Materials and Methods. Since these are patient-derived skin fibroblasts, maintaining equal numbers in each experiment is challenging. Revised graphs for orbital fibroblasts and CCL210 have been added in the new Figures 1B and 1C.

      • For the same set of experiments, please clarify and consistently describe the conditions that promote PC: 12hs serum starvation as described in M&M? Or 24hs as described in the text? Or 16 as described in figure legend 1? Or 24hs as described in supp figure 2? Response: We serum-starved the cells overnight, and this is also mentioned in the manuscript.

      • Please confirm in figure legends and M&M that 100 cells per group were counted. Response: We measured only 100 cells per cell line in Supplementary Figure S1B. To eliminate any confusion, we have now created a superplot for cilia analysis. Each small dot represents the PC length from an individual cell, and each large dot represents the average of the small dots for one cell line. An unpaired two-tailed t-test was performed on the small dots (mean ± SD).

      • Figure 2 should also provide lower magnification to show several cells per field. Response: Foreskin fibroblasts treated with TGF-β1 are added in S2A.

      • How do you explain that the increase in length of primary cilia after siACTA2 doesn't change COL1A1? Wouldn't it be a good approach to also check by Western Blot? Response: We believe that depletion of aSMA was sufficient to reduce the PC length for the reason described earlier (Avasthi and Marshall, 2012), but was not sufficient enough to change COL1A1 level. We added the western blot in Supplementary Figure S8B.

      • Once more, figure 5 will benefit from low mag images. How consistent is the effect of LiCl in the cultured cells? What is the percentage of rescued cells? Response: LiCl treatment was consistent for almost all the cells (~95%) as shown below and added in S4A.

      • Figure 5, panels F and G need better explanation in the results text as well as in the figure legend. Response: We added now.

      • 9) Some figures/supp figures are wrongly referenced in the text. *

      __ Response:__ We carefully revised the manuscript and corrected the references.

      10) Figure 6, panel A is confusing. Is it a comparison between SSC skin fibroblasts and foreskin fibroblasts? Maybe show labels on the panel.

      __ Response:__ We updated the figure legend for Panel A in Figure 6.

      11) Where is Figure 8 mentioned in the text?

      __ Response:__ In the discussion section.

      12) The work will benefit from an initial paragraph in the discussion enumerating the findings and a summary of the conclusion at the end.

      Response: We agree and modified the discussion accordingly.

      13) The nintedanib experiments are not described in the results section at all.

      Response: All nintedanib experiments are now included in Figure S5C-F and are described in the Results section.

      Significance

      Reviewer #3 (Significance (Required)): Beyond the lack of in situ ciliary expression assessment, the work is exciting, and the potential implications of treating/preventing fibrosis with small molecules to modulate ciliary length could be transformative in the field. Furthermore, there are a few HDAC6 inhibitors already in clinical trials for different tumors, which increases the significance of the work.

      Response: Thank you for your encouraging comments regarding the potential impact of our findings. We agree that the therapeutic implications of modulating ciliary length, particularly using small molecules such as HDAC6 inhibitors already in clinical trials, could be transformative in the context of fibrosis. We also acknowledge the importance of in situ assessment of ciliary expression and plan to incorporate such analyses in future studies to further strengthen our findings.

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      Referee #3

      Evidence, reproducibility and clarity

      Summary:

      The author's main research topic in this work is the relationship between ciliary length and the level of fibrosis. Fibrotic samples show shorter primary cilia, profibrotic treatment with TGFB decreases the ciliary length, and posterior dedifferentiation of fibroblasts shows longer cilia. Cells with a decrease of αSMA by using siACTA2 siRNA, also show increased ciliary length. Most importantly, inducing the increase of ciliary length with LiCl or Tubacin has an inverse association with fibrosis phenotypes. The modulation of primary cilia length may represent a potential therapeutic strategy for fibrosis-associated diseases.

      The premise is relevant and exciting, and the methods are appropriate. The experiments partially sustain the conclusion. The results open a new potential area for studying fibrosis. The tables and figures aid in understanding the paper. The paper is clear and easy to read for a basic research specialized audience.

      Major comments:

      1. Need to demonstrate if the fibrotic phenotypes seen are produced through a ciliary-dependent mechanism. For example, to see if LiCl effects on Cgn1 are through ciliary expression or by other mechanisms. To achieve that objective, The authors should repeat the experiments in cells with a knockdown or knockout of ciliary proteins such as IFT20, IFT88, etc. The same approach should be applied to the tubacin experiments.
      2. The use of LiCl to increase ciliary length is complicated. What are the molecular mechanisms underlying this effect? It is known that it may be affecting GSK-3b, which can have other ciliary-independent effects. Therefore, using ciliary KO/KD cells (IFT88 or IFT20) as controls may help assess the specificity of the proposed treatments.
      3. Also, assessing the frequency of ciliary-expressing cells is important. That may give another variable important to predict fibrotic phenotypes. Or do 100% of the cultured cells express cilia in those conditions?
      4. Have the authors evaluated if TGF-b1 treatments induce cell cycle re-entry and proliferation in these experimental conditions? This is important to exclude ciliary resorption due to cell cycle re-entry instead of the myofibroblast activation process.
      5. The authors described that they focused on the genes that are affected in opposite ways (supp table 4), but TEAD2, MICALL1, and HDAC6 are not listed in that table.

      Minor comments:

      1. Figure 1A,B,C should also show lower magnification images where several cells/field are visualized.
      2. The number of patients analyzed is not clear. For example, M&M describes 5 healthy and 8 SSc, but only 3 and 4 are shown in the figure. Furthermore, for orbital fibrosis, 2 healthy vs. 2 TAO are mentioned in the figure legend, but only one of each showed. Finally, the healthy control for lung fibroblast seems to be 3 independent experiments of the CCL210 cell line; please show the three independent controls and clarify on the X-axis and in the figure legend that these are CCL210 cells.
      3. For the same set of experiments, please clarify and consistently describe the conditions that promote PC: 12hs serum starvation as described in M&M? Or 24hs as described in the text? Or 16 as described in figure legend 1? Or 24hs as described in supp figure 2?
      4. Please confirm in figure legends and M&M that 100 cells per group were counted.
      5. Figure 2 should also provide lower magnification to show several cells per field.
      6. How do you explain that the increase in length of primary cilia after siACTA2 doesn't change COL1A1? Wouldn't it be a good approach to also check by Western Blot?
      7. Once more, figure 5 will benefit from low mag images. How consistent is the effect of LiCl in the cultured cells? What is the percentage of rescued cells?
      8. Figure 5, panels F and G need better explanation in the results text as well as in the figure legend.
      9. Some figures/supp figures are wrongly referenced in the text.
      10. Figure 6, panel A is confusing. Is it a comparison between SSC skin fibroblasts and foreskin fibroblasts? Maybe show labels on the panel.
      11. Where is Figure 8 mentioned in the text?
      12. The work will benefit from an initial paragraph in the discussion enumerating the findings and a summary of the conclusion at the end.
      13. The nintedanib experiments are not described in the results section at all.

      Significance

      Beyond the lack of in situ ciliary expression assessment, the work is exciting, and the potential implications of treating/preventing fibrosis with small molecules to modulate ciliary length could be transformative in the field. Furthermore, there are a few HDAC6 inhibitors already in clinical trials for different tumors, which increases the significance of the work.

      Expertise: primary cilium functions, cell biology, cancer biology

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      Referee #2

      Evidence, reproducibility and clarity

      This is an interesting paper that appears to show that explanted fibroblasts from a range of fibrotic conditions exhibit a reduction in the length of their primary cilia (PC). The paper employs a number of different experimental approaches that appear to show that the modulation of fibroblast/myofibroblast differentiation is associated with alterations in PC length. The rational for the study is that actin polymerization has previously been associated with PC length. The authors suggest that modulation of PC dynamics may represent a potential theraputic strategy for fibrotic disease. To me that seems like a big jump.

      Major concerns.

      I found the paper to be rather muddled and its presentation made if somewhat difficult to follow. For example, the Figures are disorganised (Fig 1 is a great example of this) and there was reference to Sup data that appeared out of order (eg Sup Fig 2 appeared before Sup Fig 1 in the text). Images in a single figure should be the same size. currently they are almost random and us different magnifications. Overall, the paper needs to be better organised.

      I have some significant concerns about how the PC length data was generated. To my mind the length may be hard to determine from the type of images shown in the paper (which may represent the best images?). Some of the images presented appear to show shorter, fatter PCs in the cells from fibrosis cases. Is this real or is it some kind of artefact? Would a shorter, fatter PCs have a similar or larger surface area? What would be the consequence of this?

      I am confused as to exactly what is meant by matched healthy controls. Age, sex and ethnicity, where stated seem to be very variable? What are CCL210 fibroblasts?

      What does a change in PC length signify? DO shot PC foe a cellular transition or are they a consequence of it? What would happen is you targeted PCs with a drug and that influenced the length on all cell types? Is the effec on PC fibroblast specific?

      Minor concerns

      Page 4 second paragraph. I think it should be clarified that it is this group who have suggested a link between PCs and myofibroblast transition?

      Page 4 second paragraph. The use of the word "remarkably' is a bit subjective.

      Reference 27 is a paper on multiciliogenesis rather than primary ciliogenesis.

      Figure 1 panel D. Make the image with the same sized vertical scale

      Significance

      To my mind this is a novel paper and the date presented in it may be of interest to the cilia community as well as to the fibrosis field. This could be considered to be a significant advance and I am unaware that other groups are actively working in this area.

      Presentation of the data in the current form does not instil confidence in the work.

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      Referee #1

      Evidence, reproducibility and clarity

      Summary

      The manuscript by Verma et al. describes the involvement of primary cilia length control in driving pro-fibrotic progression of fibroblasts in fibrotic diseases. This is shown in primary cells from several organs from patients, suffering from different fibrotic diseases. They demonstrate that primary cilia are shorter in fibroblasts from different fibrotic conditions and that pro-fibrotic signaling, as exemplified by TGFb stimulation, causes shortening of the cilium. Vice versa, elongation of the cilium via different pharmacological substances reverses the pro-fibrotic phenotype.

      Major comments

      1. To reliably quantify the ciliary length in different cell types, and in independent ciliary marker needs to be included for comparison and the ciliary base needs to be labeled (e.g., -TUBULIN). This needs to combined with a non-biased, high-throughput analysis, e.g., CiliaQ,
      2. As mentioned in the study, TGF has been implicated to drive myofibroblast transition. Thus TGF stimulate ciliary signaling in the presented primary cells? The authors should provide a read-out for TGF signaling in the cilium (ICC fro protein phosphorylation etc.). Furthermore, canonical ciliary signaling pathways have been suggested to act as fibrotic drivers, such as Hedgehog and Wnt signaling - does stimulation of these pathways evoke a similar effect?
      3. Does TGF induce cell proliferation? If yes, this would force cilium disassembly and, thereby, reduce ciliary length, which is independent of a "shortening" mechanism proposed by the authors.
      4. As PGE2 has been shown to signal through EP4 receptors in the cilium, is the restoration of primary cilia length due to ciliary signaling?
      5. Primary cilia length is regulated by cAMP signaling in the cilium vs. cytoplasm - does cAMP signaling play a role in this context? PGE2 is potent stimulator of cAMP synthesis - does this underlie the rescue of primary cilia length?
      6. The authors describe that they wanted to investigate how aSMA impacted primary cilia length. They only provide a knock-down experiment and measured ciliary length, but the mechanistic insight is missing. How does loss of aSMA expression control ciliary length?
      7. The authors used LiCl in their experiments, which supposedly control Hh signaling. Coming back to my second questions, is this Hh-dependent? And what is the common denominator with respect to TGF signaling? And how is this mechanistically connected to actin and microtubule polymerization?
      8. How was the SMA Mean intensity determined?
      9. Fig: 1D: Statistical test is missing in Figure Legend and presentation of the p-values for the left graph is confusing.
      10. Some graphs are presented {plus minus} SD and some {plus minus} SEM, but this is not correctly stated in the Material & Methods Part.
      11. Fig. 4D&E: Statistical test is missing in Figure Legend.

      Minor comments

      • In general, text should be checked again for spelling mistakes and sentences may be re-written to promote readability. In particular, this applies to the discussion.
      • Figure Legends are not written consistently, information is missing (e.g., statistical tests, see above).
      • Figures should be checked again and all text should be the same size and alignment of images should be improved.

      Significance

      The authors present a novel connection between the regulation of primary cilia length and fibrogenesis. However, the study generally lacks mechanistic insight, in particular on how TGF signaling, SMA expression, and ciliary length control are connected. The spatial organization of the proposed signaling components is also not clear - is this a ciliary signaling pathway? If so, how does it interact with cytoplasmic signaling and vice versa?

    1. References

      v1.1 Update

      The following references have been added:

      1. Food and Drug Administration, BeiGene. TEVIMBRA (tislelizumab) prescribing information. Available: https://www.accessdata.fda.gov/scripts/cder/daf/index.cfm?event=overview.process&ApplNo=761380 Accessed 5/12/25

      2. Food and Drug Administration, Astellas. VYLOY (zolbetuximab-clzb) prescribing information. Available: https://www.accessdata.fda.gov/scripts/cder/daf/index.cfm?event=overview.process&ApplNo=761365 Accessed 5/8/25

      3. Food and Drug Administration, Merck & Co. KEYTRUDA (pembrolizumab) prescribing information. Available: https://www.accessdata.fda.gov/scripts/cder/daf/index.cfm?event=overview.process&ApplNo=125514 Accessed 1/8/25

      4. Liu L, Woo Y, D’Apuzzo M, Melstrom L, Raoof M, Liang Y, et al. Immunotherapy-Based Neoadjuvant Treatment of Advanced Microsatellite Instability–High Gastric Cancer: A Case Series. Journal of the National Comprehensive Cancer Network. 2022;20(8):857-65.

      5. Kelly RJ, Lee J, Bang Y-J, Almhanna K, Blum-Murphy M, Catenacci DV, et al. Safety and efficacy of durvalumab and tremelimumab alone or in combination in patients with advanced gastric and gastroesophageal junction adenocarcinoma. Clinical Cancer Research. 2020;26(4):846-54.

      6. Moehler M, Oh DY, Kato K, Arkenau T, Tabernero J, Lee KW, Rha SY, Hirano H, Spigel D, Yamaguchi K, Wyrwicz L. First-Line Tislelizumab Plus Chemotherapy for Advanced Gastric Cancer with Programmed Death-Ligand 1 Expression≥ 1%: A Retrospective Analysis of RATIONALE-305. Advances in Therapy. 2025 Mar 13:1-21.

      7. Shitara K, Lordick F, Bang YJ, Enzinger P, Ilson D, Shah MA, Van Cutsem E, Xu RH, Aprile G, Xu J, Chao J. Zolbetuximab plus mFOLFOX6 in patients with CLDN18. 2-positive, HER2-negative, untreated, locally advanced unresectable or metastatic gastric or gastro-oesophageal junction adenocarcinoma (SPOTLIGHT): a multicentre, randomised, double-blind, phase 3 trial. The Lancet. 2023 May 20;401(10389):1655-68.

      8. Rha SY, Oh D-Y, Yañez P, Bai Y, Ryu M-H, Lee J, et al. Pembrolizumab plus chemotherapy versus placebo plus chemotherapy for HER2-negative advanced gastric cancer (KEYNOTE-859): a multicentre, randomised, double-blind, phase 3 trial. The Lancet Oncology. 2023;24(11):1181-95.

      9. Shen L, Kato K, Kim S-B, Ajani JA, Zhao K, He Z, et al. Tislelizumab versus chemotherapy as second-line treatment for advanced or metastatic esophageal squamous cell carcinoma (RATIONALE-302): a randomized phase III study. Journal of clinical oncology. 2022;40(26):3065-76

      10. Janjigian YY, Kawazoe A, Bai Y, Xu J, Lonardi S, Metges JP, et al. Pembrolizumab plus trastuzumab and chemotherapy for HER2-positive gastric or gastro-oesophageal junction adenocarcinoma: interim analyses from the phase 3 KEYNOTE-811 randomised placebo-controlled trial. The Lancet. 2023;402(10418):2197-208

      11. European Medicines Agency. KEYTRUDA (pembrolizumab) product information . Available: https://www.ema.europa.eu/en/medicines/human/EPAR/keytruda#authorisation-details Accessed 1/8/25

      12. Kelley RK, Ueno M, Yoo C, Finn RS, Furuse J, Ren Z, et al. Pembrolizumab in combination with gemcitabine and cisplatin compared with gemcitabine and cisplatin alone for patients with advanced biliary tract cancer (KEYNOTE-966): a randomised, double-blind, placebo-controlled, phase 3 trial. The Lancet. 2023;401(10391):1853-65

      13. Andre T, Elez E, Van Cutsem E, Jensen LH, Bennouna J, Mendez G, Schenker M, de la Fouchardiere C, Limon ML, Yoshino T, Li J. Nivolumab plus Ipilimumab in Microsatellite-Instability–High Metastatic Colorectal Cancer. New England Journal of Medicine. 2024 Nov 28;391(21):2014-26.

      14. Food and Drug Administration, Bristol Myers Squibb Company. OPDIVO (nivolumab) prescribing information. Available: https://www.accessdata.fda.gov/scripts/cder/daf/index.cfm?event=overview.process&ApplNo=125554 Accessed 5/14/25

      15. Food and Drug Administration, Bristol Myers Squibb Company. YERVOY (ipilimumab) prescribing information. Available: https://www.accessdata.fda.gov/scripts/cder/daf/index.cfm?event=overview.process&ApplNo=125377 Accessed 5/14/25

    1. The WTO

      The WTO is an intergovernmental organization that was created to help settle trade disputes between countries. Any given WTO agreement is meant to ensure that trade should be: 1. nondiscriminatory between products produced domestically and abroad, 2. predictable and transparent, 3. more competitive 4. more beneficial for less developed countries, and 5. better for the environment.

    1. 菩薩若見眾生來為惱亂,當自念言:「是為我之親厚,亦是我師,益加親愛,敬心待之。何以故?彼若不加眾惱[2]惱我,則[3]我不成忍[4]辱;以是故言是我親厚,亦是我師。」

    1. Author response:

      The following is the authors’ response to the original reviews

      Public Reviews:

      Reviewer #1 (Public review):

      (1) A previously determined 2:2 heterodimeric complex of LGI1-ADAM22 was suggested to play a role in trans interactions. Could the authors discuss if the heterohexameric 3:3 LGI1-ADAM22 is more likely to represent a cis complex or a trans complex, or if both are possible?

      We noticed that there was no obvious structural feature strongly suggesting that the heterohexameric 3:3 LGI1-ADAM22 is more likely to represent a cis complex or a trans complex. Both are possible at the synapse (and similarly, for LGI3-ADAM23 at the jaxtaparanode of myelinated axons). Therefore, we revised the Introduction and Discussion sections as follows:

      Introduction: (about potential structural mechanisms of the 3:3 complex)

      “Similarly to the 2:2 complex, the 3:3 complex might serve as an extracellular scaffold to stabilize Kv1 channels or AMPA receptors in a trans-synaptic fashion. In addition, the 3:3 assembly in a cis fashion on the same membrane might regulate the accumulation of Kv1 channel complexes at axon initial segment. However, no clear evidence to prove these potential mechanistic roles of the 3:3 assembly has been provided, and the three-dimensional structure of the 3:3 complex has not yet been determined.”

      Discussion: (about a role of the LGI3–ADAM23 complex at the jaxtaparanode of myelinated axons)

      “In this context, as discussed in (30), either or both of the 2:2 and 3:3 complexes might be formed in a trans fashion at the juxtaparanode of myelinated axons and bridge the axon and the innermost myelin membrane. Alternatively, the 3:3 complex formed in a cis fashion might positively regulate the clustering of the axonal Kv channels at the juxtaparanode, possibly in a similar manner at the axon initial segment.”

      *Ref. 30: Y. Miyazaki et al., Oligodendrocyte-derived LGI3 and its receptor ADAM23 organize juxtaparanodal Kv1 channel clustering for short-term synaptic plasticity. Cell Rep 43, 113634 (2024).

      (2) It is not entirely clear to me if the LGI1-ADAM22 complex is also crosslinked in the HS-AFM experiments. Could this be more clearly indicated? In addition, if this is the case, could an explanation be given about how the complex can still dissociate?

      Thank you for the constructive suggestions. A non-crosslinked 3:3 LGI-ADAM22 complex was used for HS-AFM observations. To clarify the sample used for HS-AFM, we have modified the text as follows.

      P.8 “Dynamics of the LGI1‒ADAM22 higher-order complex observed by HS-AFM

      HS-AFM images of gel filtration chromatography fractions containing the 3:3 LGI1-ADAM22<sub>ECD</sub> complex (not chemically crosslinked with glutaraldehyde) predominantly…”

      P.10 Materials and methods

      “HS-AFM observations of the LGI1–ADAM22<sub>ECD</sub> complex (not chemically crosslinked with glutaraldehyde) were conducted on AP-mica,…”

      (3) The LGI1 and ADAM22 are of similar size. To me, this complicates the interpretation of dissociation of the complex in the HS-AFM data. How is the overinterpretation of this data prevented? In other words, what confidence do the authors have in the dissociation steps in the HS-AFM data?

      Our criteria for assigning HS-AFM images to the 3:3 LGI1–ADAM22<sub>ECD</sub> complex were based on a comparison of the simulated AFM image of the 3:3 complex obtained by cryo-EM. The automatized fitting process (42) identifies the optimal orientation of cryo-EM images that closely matches the HS-AFM image. In the present study, the concordance coefficient (CC) reached 0.8, indicating that the protein orientation in HS-AFM images of the 3:3 complex was objectively satisfactory.

      Regarding the dissociation step of ADAM22 from the 3:3 complex, we carefully analyzed the HS-AFM videos frame by frame and observed that the protrusion corresponding to ADAM22 in the 3:3 complex disappeared at a specific frame (4.5 s in the third molecule in Movie S1). The dissociation steps of ADAM22 were further confirmed by integrating multiple independent HS-AFM experiments and observations. Thus, although HS-AFM images alone cannot determine the orientation of LGI1 and ADAM22 in the 3:3 complex, the comparison of cryo-EM images with simulated AFM images enables objective assignment and orientation of proteins in the 3:3 complex through automated fitting.

      *Ref. 42: R. Amyot et al., Flechsig, Simulation atomic force microscopy for atomic reconstruction of biomolecular structures from resolution-limited experimental images. PLoS Comput Biol 18, e1009970 (2022).

      (4) What is the "LGI1 collapse" mentioned in Figure 4c?

      Thank you for the constructive suggestions. The term “LGI1 collapse” was intended the dissociation of LGI1 from the 3:3 complex. To avoid confusion, we have revised it to “LGI1 release”.

      (5) Am I correct that the structure indicates that the trimerization is entirely organized by LGI1? This would suggest LGI1 trimerizes on its own. Can this be discussed? Has this been observed?

      Yes. The present cryo-EM structure of the 3:3 complex indicates that the trimerization can be entirely organized by LGI1. In addition, during the HS-AFM imaging, the triangle shape seems to be maintained even if one ADAM22<sub>ECD</sub> molecule is released. These findings suggest the possibility that LGI1 could trimerize on its own although this possibility could not be tested due to the difficulty in the expression of the full-length LGI1 alone for biophysical analysis in our hands. On the other hand, considering the dynamic property of the 3:3 complex and spatial alignment of LGI1LRR and ADAM22, we cannot exclude the possibility that ADAM22 could act as a platform to facilitate the intermolecular interaction between LGI1<sub>LRR</sub> and LGI1*<sub>EPTP</sub> for the trimerization of LGI1. This discussion was added in the first paragraph of the subsection "Dynamics of the LGI1–ADAM22 higher-order complex by HS-AFM".

      (6) C3 symmetry was not applied in the cryo-EM reconstruction of the heterohexameric 3:3 LGI1-ADAM22 complex. How much is the complex deviating from C3 symmetry? What interactions stabilize the specific trimeric conformation reconstructed here, compared to other trimeric conformations?

      According to this comment, we compared the non-symmetric, present cryo-EM structure to the previously calculated _C_3 symmetry-restrained structure based on small-angle X-ray scattering analysis and the _C_3 symmetric structure generated by AlphaFold3. Their differences in the domain or protomer configuration are illustrated in Fig. S9.

      We did not find interactions that could obviously stabilize the specific trimeric conformation but the closure motion of LGI1<sub>LRR</sub> (relative to LGI1<sub>EPTP</sub>) in chain F appears to locate it in close proximity to LGI1LRR in chain D to make the triangular assembly slightly more compact. This (partly) compact configuration might stabilize the non-symmetric trimeric configuration observed in the cryo-EM structure. This was described in the last sentence in the subsection "Cryo-EM structure of the 3:3 LGI1– ADAM22<sub>ECD</sub> complex".

      Reviewer #2 (public review):

      The functional significance of these two complexes in the context of synapse remains speculative.

      To assess the functional significance of the 3:3 complex, we spent time and effort designing mutations that solely inhibit the 3:3 assembly but failed to find such mutations. In this paper, we just focused on structural characterization of the 3:3 complex.

      Additionally, the structural presentations in Figures 1-3 (especially Figures 2-3) lack the clarity needed for general readers to fully understand the authors' key points. Enhancing the quality of these visual representations would greatly improve accessibility and comprehension.

      We made an effort to improve Figures 1-3 accordingly. Specifically, we revised them based on the strategy suggested in the Editorial comment regarding this reviewer's comment.

      Editorial comments:

      We noticed that in the reconstruction of the 3:3 complex, which is claimed to be at 3.8A resolution, beta-strands are not separated in the map and local resolution estimates vary from 6-10A. Please clarify.

      We revised Fig. S8 to show the local resolution and volume quality, which correspond to nominal resolution of 3.8 Å, estimated from gold-standard FSC.

      Reviewer #1 (Recommendations for the authors):

      (1) PDB validation reports should be presented to allow further validation

      The PDB validation reports were attached to the revised manuscript (uploaded as "related manuscript file").

      (2) In Figure 4, models below the AFM figures are difficult to see because of the light coloring. In addition, in panel c, the orientation of some of the parts of the models below the 19.2 and 34.5 s. panels do not seem to correlate with the AFM figures. Could the models be adjusted so that they represent the data better?

      Thank you for the constructive suggestions. According to the Reviewer’s comments, we have revised the AFM figures (Fig. 4).

      (3) References are sometimes missing for important statements. Please check throughout.

      Some examples:

      P3, "it has been suggested that the 3:3 complex regulates the density of synaptic molecules such as scaffolding proteins and synaptic vesicles".

      P3. "Furthermore, LGI1 forms a complex with the voltage-gated potassium channel (VGKC) through ADAM22/23".

      According to this comment, we rewrote the description about potential physiological roles of the 3:3 complex and added references as follows:

      "Similarly to the 2:2 complex, the 3:3 complex might serve as an extracellular scaffold to stabilize Kv1 channels or AMPA receptors in a trans-synaptic fashion (9, 17, 19). In addition, the 3:3 assembly in a cis fashion on the same membrane might regulate the accumulation of Kv1 channel complexes at axon initial segment (18, 20). However, no clear evidence to prove these potential mechanistic roles of the 3:3 assembly has been provided, and the three-dimensional structure of the 3:3 complex has not yet been determined."

      We also added references to the following sentences:

      p.2, (the last sentence in the first paragraph of the Introduction) “Additionally, some epilepsy-related mutations have been identified in genes encoding non-ion channel proteins such as LGI1 (4-7).”

      p.3, ln 4-5, “The metalloprotease-like domain interacts with the EPTP domain of LGI1 in the extracellular space (11, 14).”

      p.3, ln 9-10, “Furthermore, LGI1 forms a complex with the voltage-gated potassium channel (VGKC) through ADAM22/23 (9, 17, 18)”

      p.3, ln 20-22, “The results revealed the structural basis of the interaction between the EPTP domain of one LGI1 and the LRR domain of the other LGI1, as well as the interaction between the EPTP domain of LGI1 and the metalloproteinase-like domain of ADAM22 (14)”

      (4) S5 for clarity please add an overview of the complex highlighting where the different parts shown in the panels are located.

      Fig. S5 was modified accordingly. Every panel showing a zoom-up view was indicated by a box in an overview of the complex.

      (5) S7 a+b, also here add models for the structures to indicate which parts are shown.

      Could labels be added to highlight important parts?

      We added an overview of the complex with boxes that indicate the parts shown as the panels, according to this comment. We also added labels to highlight residues that are important for the LGI1<sub>EPTP</sub>–ADAM22<sub>ECD</sub> interaction in the panel showing the LGI1<sub>EPTP</sub>–ADAM22<sub>ECD</sub> interface.

      (6) S7c also shows the cartoon of the structure. How is it possible that the local resolution is not much higher than 6 Å? The overall resolution was 3.8 Å? This looks like a figure of the density plotted at a low level, and not as stated a "surface representation". Could an extra panel be shown of the density plotted at a higher level? Also, please add Å to the legend in this figure.

      Local resolution maps of the 3:3 LGI1-ADAM22<sub>ECD</sub> complex were shown as Fig. S8 in the revised manuscript. According to this comment, the distribution of the resolution was plotted onto the density at high (0.06) and low (0.03) levels. "Å" was added to the legend in the figure.

      Reviewer #2 (Recommendations for the authors):

      (1) The study was conducted using the ectodomain (ECD) of ADAM22. It remains unclear whether the 3:3 complex could form if the transmembrane domain (TMD) of ADAM22 were included. In other words, it is difficult to assess whether the observed 3:3 complex represents plausible cis interactions.

      As mentioned in our reply to the first comment from Reviewer #1, we noticed that there was no obvious structural feature strongly suggesting that the heterohexameric 3:3 LGI1–ADAM22 is more likely to represent a cis complex or a trans complex. Both are possible at the synapse (and similarly, for LGI3–ADAM23 at the jaxtaparanode of myelinated axons). Therefore, we revised the Introduction and Discussion sections as follows:

      Introduction: (about potential structural mechanisms of the 3:3 complex)

      “Similarly to the 2:2 complex, the 3:3 complex might serve as an extracellular scaffold to stabilize Kv1 channels or AMPA receptors in a trans-synaptic fashion. In addition, the 3:3 assembly in a cis fashion on the same membrane might regulate the accumulation of Kv1 channel complexes at axon initial segment. However, no clear evidence to prove these potential mechanistic roles of the 3:3 assembly has been provided, and the three-dimensional structure of the 3:3 complex has not yet been determined.”

      Discussion: (about a role of the LGI3–ADAM23 complex at the jaxtaparanode of myelinated axons)

      “In this context, as discussed in (30), either or both of the 2:2 and 3:3 complexes might be formed in a trans fashion at the juxtaparanode of myelinated axons and bridge the axon and the innermost myelin membrane. Alternatively, the 3:3 complex formed in a cis fashion might positively regulate the clustering of the axonal Kv channels at the juxtaparanode, possibly in a similar manner at the axon initial segment.”

      *Ref. 30: Y. Miyazaki et al., Oligodendrocyte-derived LGI3 and its receptor ADAM23 organize juxtaparanodal Kv1 channel clustering for short-term synaptic plasticity. Cell Rep 43, 113634 (2024).

      (2) Page 2, line 1: "...caused by genetic mutations." - Specify the mutations involved. Which genes are mutated? Providing this information would enhance clarity and context.

      According to this comment, we rephrased the sentence as follows:

      "LGI1 is linked to epilepsy, a neurological disorder that can be caused by genetic mutations of genes regulating neuronal excitability (e.g., voltage- or ligand-gated ion channels)."

      (3) The experimental strategy and data for both cryo-EM and HS-AFM are of high quality. However, improvements are needed in the cryo-EM/structural figures to enhance clarity. Structural components should be labeled, and the protein interfaces should be identified within the overall complex figures in Figures 2 and 3, as the current presentation is challenging for general readers to follow. For example, in Figure 2, panel a would benefit from clear labeling to indicate the locations of ADAM22 and LGI1. Panels b and c lack context unless the authors specify which interface corresponds to panel a. Additionally, panels e and f are unlabelled, making it difficult to interpret the figures. Improved annotations and descriptions would significantly enhance figure accessibility and comprehension.

      Thank you for the constructive suggestion for enhancing accessibility and comprehension of cryo-EM/structural figures. According to this comment, we labeled structural components and indicated the protein interfaces as boxes in the overall complex figures in Figures 2 and 3. Further, in Figure 2, the locations that panels b and c show were indicated as two boxes in the close-up view in panel a.

    1. Author response:

      The following is the authors’ response to the original reviews

      Reviewer #1:

      (1) The data are generated using ATP read-out (CTG assay). For any inhibitor of mitochondrial function, ATP assays are highly sensitive reflecting metabolic stress, yet these do not necessarily translate into cell growth inhibition using standard Trypan blue assays and tend to overestimate the effects. Please show orthogonal more robust assays of cell growth or proliferation.

      We acknowledge the sensitivity of the ATP read-out assay in reflecting metabolic stress. While additional cell growth assays such as Trypan blue exclusion could provide further insights, we believe that the current ATP assay data robustly demonstrate the effect of the IMT and venetoclax combination on cellular metabolism, which is a critical aspect of our study. The scope of our current work focused on metabolic inhibition, and we suggest that future studies could further explore cell proliferation assays to complement these findings.

      (2) It is concluded that AML cells do not utilize glucose for ATP production. Please provide formal measurements of glycolysis/lactate upon combinatorial treatment.

      We appreciate the reviewer’s suggestion to include glycolysis and lactate measurements, which could indeed add further granularity to our metabolic analysis. However, the primary focus of our study is on mitochondrial function and oxidative phosphorylation (OXPHOS) in AML cells treated with IMT and venetoclax. We believe the data presented in Figure 3 provide strong support for the conclusion that glycolysis is not a major energy source in these cells.

      Specifically, in Figure 3C, we demonstrate that AML cells maintain ATP levels and viability when cultured in galactose, a condition that restricts ATP production through glycolysis and forces cells to rely on OXPHOS. This result strongly suggests that these AML cells are not dependent on glycolysis for ATP production. Furthermore, in Supplementary Figure S3B, we show that oxygen consumption rate (OCR) measurements remain stable in the presence of excess glucose, further supporting our conclusion that the cells do not switch to glycolysis when OXPHOS is inhibited.

      These findings collectively indicate a primary reliance on OXPHOS for energy generation in AML cells, consistent with our study’s objectives to explore mitochondrial dependency and the therapeutic potential of targeting mitochondrial transcription in AML. Future studies could certainly expand on these insights by incorporating a more detailed analysis of glycolytic flux and lactate production under combinatorial treatment, but we believe the current data are sufficient to support our main conclusions.

      (3) The transcriptome data are shown without any analysis of pathways. The conclusion from this data beyond the higher number of genes impacted in the combination arm is unclear. Please provide analysis for example GO pathways and interpret in the context of the drugs' mechanism of action.

      In response to the reviewer’s question, we have added gene ontology (GO) pathway analysis to clarify the transcriptomic impact of our combination treatment with IMT and venetoclax. Functional annotation identified significant enrichment in pathways relevant to innate immune response, mitochondrial function, and cellular signaling processes. Specifically, pathways associated with immune defense, mitochondrial signaling, and intracellular signaling were notably affected. These findings suggest that the combination treatment not only disrupts cellular energy metabolism but also potentially primes immune signaling mechanisms. This aligns with the proposed mechanism, where IMT targets mitochondrial transcription and venetoclax induces apoptosis, together enhancing sensitivity in AML cells. The enriched pathways, therefore, support the mechanism of action of both drugs, showing how the combined inhibition of BCL-2 and mitochondrial transcription creates a compounded cellular disruption that enhances the therapeutic effect.

      (4) Please demonstrate (could be in supplement) matrix of combination to support the statement that the combination is synergistic using Bliss index. The actual Bliss values are missing.

      For the revision, we have now included a matrix of combination treatment effects with the corresponding Bliss synergy index values to substantiate our claim of synergy between IMT and venetoclax. This analysis, provided in the supplement, demonstrates that the observed effects exceed the expected additive impact of each drug alone, as calculated by the Bliss independence model. Specifically, the Bliss values confirm a synergistic interaction in venetoclax-sensitive AML cell lines, highlighting that the combined treatment significantly enhances inhibition of cell viability and apoptosis induction compared to single treatments. This data supports our interpretation of synergy and strengthens the mechanistic conclusions drawn from our findings on the combination therapy’s efficacy.

      (5) Please show KG1 data (OCR), here or in Supplement.

      In response to the reviewer’s request to include OCR data for the KG-1 cell line, we would like to clarify that OCR measurements were attempted; however, they did not yield conclusive results. This is noted in the revised manuscript (Results section), where we explain that the KG-1 cell line did not provide usable OCR data, likely due to limitations in detecting reliable mitochondrial respiration in this particular line under our experimental conditions. Therefore, we were unable to include KG-1 OCR data in the main figures or the supplement.

      Reviewer #2:

      (1) It's important that the authors show that the drug's effects in AML are due to on-target inhibition. It's critical that they show that IMT actually inhibits the mito polymerase in the AML cells in the dose range employed.

      We appreciate the importance of demonstrating on-target inhibition of mitochondrial RNA polymerase by IMT1, especially in light of the detailed characterization of IMT1b, a closely related compound, as presented in Bonekamp et al., Nature 2020. The work by Bonekamp et al. established the specificity and efficacy of IMT1b in targeting mitochondrial RNA polymerase across various tumor models. Building on these findings, we designed our study to primarily evaluate the combinatorial efficacy of IMT1 with venetoclax in AML models, assuming a similar mechanism of action as described for IMT1b. While direct confirmation of on-target inhibition in AML cells by IMT1 would undoubtedly provide additional mechanistic insight, we focused on translational aspects in this study. We believe that the foundational work provided by Bonekamp et al. supports the assumption of on-target effects by IMT1, and we suggest that future studies could explicitly verify this in the context of AML.

      (2) For Fig 1, the stated synergism between Venetoclax (Vex) and IMT in p53 mutant THP1 cells is really not evident, despite what the statistical analysis says. In some ways, the more interesting conclusion is that inhibiting mitochondrial transcription does NOT potentiate the efficacy of Bcl2 inhibition in TP53 mutant AML.

      We appreciate the reviewer’s observation regarding the lack of evident synergy between IMT and venetoclax in TP53 mutant THP-1 cells. In line with this comment, we have now expanded the discussion to emphasize that, while statistical analysis suggested a potential interaction, the biological response in TP53 mutant cells was minimal. This contrasts with the strong synergy observed in TP53 wild-type cell lines, such as MV4-11 and MOLM-13. We have now highlighted that TP53 mutation status may limit the effectiveness of mitochondrial transcription inhibition in potentiating BCL-2 inhibition. This addition underscores the importance of mutation profiles, such as TP53 status, in predicting response to combination therapies in AML and is now clearly addressed in the revised discussion.

      (3) They combine IMT with Vex, but Vex plus azacytidine or decitabine is the approved therapy for AML. Any clinical trial would likely start with this backbone (like Vex+Aza). They should test combinations of IMT with Vex/Aza or Vex/Dec.

      While we recognize the importance of testing IMT in combination with clinically approved therapies like Vex+Aza, our current study was designed to explore the potential of IMT in combination with venetoclax alone. Expanding to other combinations would be an excellent direction for future research but is beyond the scope of our current investigation.

      (4) It's interesting that AML cell lines do not show any reliance on ATP generation from glycolysis, but would this still be the case when OxPhos is inhibited with IMT? Such a simple experiment would be much more interesting and could help them better understand the mechanism of IMT efficacy.

      We thank the reviewer for highlighting this point regarding the reliance of AML cell lines on glycolysis under OxPhos inhibition. In our study, we observed that AML cells predominantly rely on OxPhos, and we did test for ATP production in conditions that favored glycolysis by growing AML cells with galactose instead of glucose in the medium. As described in the manuscript, we did not observe significant ATP production or cell viability from glycolysis, even under these conditions. This finding suggests that AML cells have a low capacity to adapt to glycolytic ATP generation when OxPhos is disrupted by IMT, reinforcing the view that they are highly dependent on mitochondrial function for energy production. We agree that this adaptation—or lack thereof—is an intriguing aspect of IMT efficacy in targeting energy metabolism in AML cells, and we have clarified this point in the discussion.

      (5) OxPhos measurements need statistical analyses.

      We appreciate the reviewer’s suggestion to include statistical analyses for the OXPHOS measurements. We would like to clarify that statistical analyses were included in the initial submission. These are detailed in Figure 3 and its legend, as well as in the Statistical Analysis section, where we specify methods such as the calculation of standard error across replicates. This approach was implemented to ensure the rigor of our OCR data and its conclusions on OXPHOS inhibition in AML cells.

      (6) Given that the combo-treated mice do not exhibit much leukemia in the blood through ~180 days, and yet start dying after 100 days, the authors should comment on this, given that the bone marrow has been shown to be a refuge that protects leukemia cells from various therapies.

      We thank the reviewer for highlighting the observed discrepancy between peripheral blood leukemia levels and survival in combo-treated mice. While leukemic cells were minimally detected in the blood up to approximately 180 days, treated mice began to show signs of disease progression and reduced survival around 100 days. This may suggest that residual leukemic cells persist within the bone marrow, which has been established as a sanctuary site for leukemic cells, providing protection from various therapies. The bone marrow environment likely supports a survival niche, enabling these residual cells to evade treatment effects and potentially initiate disease relapse. We have added this interpretation to the discussion to acknowledge the possibility of bone marrow as a protective refuge, which may limit the full eradication of leukemia in these models despite apparent peripheral blood clearance.

      (7) For Fig 5C, the authors should statistically compare the Combo with Vex alone.

      We have now included statistical comparisons between the combination treatment and venetoclax alone in Fig 5C to provide a clearer interpretation of the data.

      (8) The analyses of gene expression using RNAseq of harvested leukemia cells from the PDX model (Table S2), some more discussion of these results would be helpful, particularly given that neither drug is directly targeting nuclear gene expression.

      We thank the reviewer for their suggestion to discuss the RNAseq findings in more detail. In the revised manuscript, we have expanded on the functional annotation of the gene expression changes observed in leukemia cells from the PDX model following combination treatment (Table S2). The enriched pathways include innate immune involvement, mitochondrial function and immune signaling, and intracellular signaling. This suggests that while neither IMT nor venetoclax directly targets nuclear gene expression, the combined treatment induces secondary effects that alter these pathways, potentially contributing to the treatment’s efficacy in AML. This expanded discussion provides greater insight into how the drug combination impacts gene expression and cellular pathways.

      (9) We need more information on the PDX models, in terms of the classification (M1 to M6) of the patient AMLs and genetics (specific mutations, not just the genes mutated, and chromosomal alterations).

      Additional details regarding the classification and genetic background of the PDX models have been included in the manuscript to better contextualize our findings.

      (10) The authors should discuss whether or not IMT represents an improvement over other therapies intended to target Oxphos in AML (clearly, the low toxicity of IMT is a plus, at least in mice).

      We appreciate the reviewer’s suggestion to discuss IMT in comparison with other OXPHOS-targeting therapies for AML. In the revised discussion, we highlight IMT’s unique properties, particularly its low toxicity profile, which may offer advantages over other OXPHOS inhibitors. This low toxicity, demonstrated in preclinical studies, suggests that IMT might improve patient tolerability compared to existing therapies that target mitochondrial function.

      (11) The authors examined toxicity by weighing the mice and performing CBCs. Measurements of liver and kidney toxicity will be necessary for further clinical development.

      We thank the reviewer for the suggestion to further investigate liver and kidney toxicity. In our study, we assessed toxicity through regular weight monitoring and complete blood counts (CBCs) to evaluate overall health status. While additional liver and kidney toxicity measurements will indeed be important in future studies, resource limitations currently prevent us from performing these additional analyses in this model. We agree that these assessments will be essential as we progress towards clinical development, and we plan to address them in upcoming preclinical studies.

    1. Reviewer #2 (Public review):

      This study aims to elucidate the role of fibroblasts in regulating myocardium and vascular development through signaling to cardiomyocytes and endothelial cells. This focus is significant, given that fibroblasts, cardiomyocytes, and vascular endothelial cells are the three primary cell types in the heart. The authors employed a Pdgfra-CreER-controlled diphtheria toxin A (DTA) system to ablate fibroblasts at various embryonic and postnatal stages, characterizing the resulting cardiac defects, particularly in myocardium and vasculature development. Single-cell RNA sequencing (scRNA-seq) analysis of the ablated hearts identified collagen as a crucial signaling molecule from fibroblasts that influences the development of cardiomyocytes and vascular endothelial cells.

      This is an interesting manuscript; however, there are several major issues, including an over-reliance on the scRNA-seq data, which shows inconsistencies between replicates.

      Some of the major issues are described below.

      (1) The CD31 immunostaining data (Figure 3B-G) indicate a reduction in endothelial cell numbers following fibroblast deletion using PdgfraCreER+/-; RosaDTA+/- mice. However, the scRNA-seq data show no percentage change in the endothelial cell population (Figure 4D). Furthermore, while the percentage of Vas_ECs decreased in ablated samples at E16.5, the results at E18.5 were inconsistent, showing an increase in one replicate and a decrease in another, raising concerns about the reliability of the RNA-seq findings.

      (2) Similarly, while the percentage of Ven_CMs increased at E18.5, it exhibited differing trends at E16.5 (Fig. 4E), further highlighting the inconsistency of the scRNA-seq analysis with the other data.

      (3) Furthermore, the authors noted that the ablated samples had slightly higher percentages of cardiomyocytes in the G1 phase compared to controls (Fig. 4H, S11D), which aligns with the enrichment of pathways related to heart development, sarcomere organization, heart tube morphogenesis, and cell proliferation. However, it is unclear how this correlates with heart development, given that the hearts of ablated mice are significantly smaller than those of controls (Figure 3E). Additionally, the heart sections from ablated samples used for CD31/DAPI staining in Figure 3F appear much larger than those of the controls, raising further inconsistencies in the manuscript.

      (4) The manuscript relies heavily on the scRNA-seq dataset, which shows inconsistencies between the two replicates. Furthermore, the morphological and histological analyses do not align with the scRNA-seq findings.

      (5) There is a lack of mechanistic insight into how collagen, as a key signaling molecule from fibroblasts, affects the development of cardiomyocytes and vascular endothelial cells.

      (6) In Figure 1B, Col1a1 expression is observed in the epicardial cells (Figure 1A, E11.5), but this is not represented in the accompanying cartoon.

      (7) Do the PdgfraCreER+/-; RosaDTA+/- mice survive after birth when induced at E15.5, and do they exhibit any cardiac defects?

    1. Author response:

      The following is the authors’ response to the original reviews

      Reviewer #1:

      The Reviewer asks that we provide the source of PDGF-AB/BB proteins.

      We apologize for omitting such information. We now provide the source of PDGF-AB/BB in the Methods as PeproTech. In our revised manuscript we clearly state in Page 7, line 142: “Cells were then treated with recombinant human PDGF-AB (40ng/ml; PeproTech, 10770584) or -BB (20ng/ml; PeproTech, 10771918) for 5 days. “

      The Reviewer asks that we adequately report our chosen irradiation parameters suggesting that we consider (PMCID: PMC5495460) for appropriate parameter reporting.

      We thank the Reviewer for this excellent suggestion. We now provide a more detailed irradiation reporting based on the shared manuscript in Page 9, line 10, line 204.

      The Reviewer requests more details about the age range to distinguish young from old donors.

      In the Methods section of our revised manuscript, we now provide the age range for our old donors being between 53 and 67 while our younger donor population ranged between 19 and 27 years of age. These changes are reflected in Page 6, line 128: “Human degenerated NP and AF tissues (Grade IV or V on Pfirrman grade; 64.6 ±8.5 years old)) were obtained as the surgical waste from donors with discogenic pain, with each donor providing written informed consent. Healthy NP and AF cells (23.0 ±3.7 years old) were gifted by Professor Lisbet Haglund from McGill University (Tissue Biobank #2019-4896).”

      The Reviewer wonders about the rationale for using different concentrations of PDGF-AB/BB in the degenerate cell and irradiation experiments.

      We apologize for our lack of clarity. We initially treated cells with different concentrations (20 and 40 ng/ml) of PDGF-AB/BB to first establish a dose-response. From our MTT and gene expression analyses we determined that 20ng/ml was sufficient to elicit significant changes in cell proliferation markers, including MKI67, CCNB1 and CCND1. Increasing the concentration to 40 ng/ml of either growth factor did not significantly influence these parameters. However, we felt that for our bulk RNA seq experiments, we may see better changes in signaling molecules under 40ng/ml of PDGF-AB since its effects on cell growth at this concentration were maximal while PDGF-BB was maintained at 20ng/ml based on its efficacy in our mitogenic response.

      The Reviewer asks that we consider describing the effects of PDGF-AB/BB as mitigating or therapeutic rather than protective both in the title and throughout the manuscript.

      We agree with the Reviewer’s recommendation, and we have now changed the title to “Therapeutic effects of PDGF-AB/BB against cellular senescence in human intervertebral disc”. Moreover, we implemented this change in the revised manuscript as requested.

      The Reviewer believes that changes in the NP are more clinically evident (by imaging methods), despite degeneration often initiating from the AF (annulus fibrosus), e,g. through tears/microtears and would like for us to reflect this in our revised manuscript.

      We agree with the Reviewer’s comment, and we thank them for this added accuracy. On this basis, we now corrected our language in the introduction by stating in Page 4, line 68 that: “To date, the main focus of IVD cell studies has been on the NP, as changes in the NP are easily detected through imaging techniques like MRI, making it the most visible indicator of disc degeneration in clinical practice. In addition, NP plays a crucial role in the progression of IVD degeneration due to its susceptibility to significant structural and functional changes during aging and degeneration.”

      The Reviewer points out a prior study which examined the effects of X-ray irradiation on NF-kB signaling in young and aged IVDs (PMCID: PMC5495460) suggesting that we include this reference in our revised manuscript.

      We thank the Reviewer for this suggestion, and we are now referencing this elegant study in the discussion section of our revised manuscript. Thus, in page 20, line 440 we state: “ In fact, it has been shown that NF-kB signaling was elevated in mouse IVDs exposed to a single 20 Gy dose of irradiation in an ex vivo culture model.”

      The Reviewer asks that our experimental methods are described in the order of the experimental workflow. For example, section 2.2 describes RNA sequencing, which is a terminal assay. Section 2.2 may be more appropriate for detailing the methods of PDGF-AB/BB treatment, along with the rationale.

      We thank the Reviewer for pointing this out and have reorganized the Methods section accordingly.

      Reviewer #2:

      The Reviewer requests more experimental details in the methodology including the rationale for such methods/conditions as well as specific culture models utilized, substrates, cell density, and media components.

      We apologize for our lack of clarity. We now revised the methods section based on the comments.

      The Reviewer asks about the quantitative data for b-galactosidase assay and immunofluorescence of senescence-associated proteins such as P21 and P16.

      We apologize for omitting this information. We now included the quantification of P21 and P16 positive cells, which is presented in the revised Figures 4. For b-galactosidase assay, we were unable to quantify the percentage of positive cells because we did not perform nuclei staining, making it difficult to accurately determine the total cell number. Instead, we provided representative images showing the full field of view at 10X magnification using Echo microscope.

      The Reviewer requests the protein level data of PDGFRA to determine if the transcripts are being translated to protein.

      We thank the Reviewer for this suggestion. The protein expression of PDGFRA has been included in the Supplementary Figure 2. We found that PDGFRA protein levels were decreased in both NP and AF cells in response to PDGF treatments. It is known that upon binding with PDGF ligands, PDGFRA undergoes rapid internalization and degradation, a mechanism that prevents overstimulation of the signaling pathway (doi: 10.1042/BST20200004). The upregulated gene expression probably attempting to compensate for this degradation and supports continued activation of PDGFRA signaling activation, emphasizing its crucial role in response to the PDGF treatment. Thus, we implemented it in the discussion section in page 22, line486:” Interestingly, while mRNA level was increased in PDGF treated NP cells, its protein level was decreased, highlighting the complexity in PDGF receptor dynamics. Upon binding with PDGF ligands, PDGFRA is known to undergo rapid internalization and degradation, a mechanism that prevents overstimulation of the signaling pathway (Rogers and Fantauzzo 2020). The upregulated gene expression probably attempting to compensate for this degradation and supports continued activation of PDGFRA signaling activation, emphasizing its crucial role in response to the PDGF treatment.”

      The Reviewer points out that our conclusion that “PDGF do not mediate their effects via the PDGFRA” is not supported by the current data asking that further discussion, interpretation, and direct comparison of the nucleus pulposus and annulus fibrosus data sets be presented to the readers.

      We thank the Reviewer for the insightful comment. In page 20, line 432, we have corrected our language to now state: “In contrast, while PDGF treatment alleviated the senescent phenotype in AF cells, it also induced changes in pathways such as response to mechanical stimuli and neurogenesis, which were distinct from those in NP cells. This indicates that the treatment enhanced IVD functionality through different mechanisms within the two compartments.”

      The Reviewer cannot appreciate the changes in S-phase between control and treated groups.

      We apologize for the poor quality of the figure in our initial submission. We analyzed the data in S phase and included them in our revised Figures 5C and 5F.

      The Reviewer believes that discectomies are typically not performed on patients with discogenic back pain but on patients who are undergoing surgery for a herniated disc.

      We agree with the Reviewer, and we corrected our language in the revised manuscript. In Page 6, line 128, we now stated: “Human degenerated NP and AF tissues (Grade IV or V on Pfirrman grade; 64.6 ±8.5 years old)) were obtained as the surgical waste from donors with disc herniation, with each donor providing written informed consent.”

      The Reviewer asks about the protein-protein interactions in AF cells.

      We thank the Reviewer for this suggestion, and we now included it in Figure 3.

      The Reviewer requests more details about the protocol and doses for the irradiation studies.

      In the revised manuscript, we added this information in page 10, line 204.

      The Reviewer asks whether the gene expression of PDGFRA was increased or decreased in irradiated cells compared to non-irradiated cells.

      The gene expression of PDGFRA was decreased in NP cells exposed to irradiation compared to non-irradiated cells. The data are shown in Figure 4 and their description in the text is in page 17, line 411.

    1. Author response:

      The following is the authors’ response to the original reviews

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      Zhao and colleagues employ Drosophila nephrocytes as a model to investigate the effects of a high-fat diet on these podocyte-like cells. Through a highly focused analysis, they initially confirm previous research in their hands demonstrating impaired nephrocyte function and move on to observe the mislocalization of a slit diaphragmassociated protein (pyd). Employing a reporter construct, they identify the activation of the JAK/STAT signaling pathway in nephrocytes. Subsequently, the authors demonstrate the involvement of this pathway in nephrocyte function from multiple angles, using a gain-of-function construct, silencing of an inhibitor, and ectopic overexpression of a ligand. Silencing the effector Stat92E via RNAi or inhibiting JAK/ STAT with Methotrexate effectively restored impaired nephrocyte function induced by a high-fat diet, while showing no impact under normal dietary conditions.

      Strengths:

      The findings establish a link between JAK/STAT activity and the impact of a high-fat diet on nephrocytes. This nicely underscores the importance of organ crosstalk for nephrocytes and supports a potential role for JAK/STAT in diabetic nephropathy, as previously suggested by other models.

      Weaknesses:

      The analysis is overly reliant on tracer endocytosis and single lines. Immunofluorescence of slit diaphragm proteins would provide a more specific assessment of the phenotypes.

      We thank the reviewer for the positive comments and pointing out that slit diaphragm markers would provide a more specific assessment of the phenotypes. In our revised manuscript, we used Sns-mRuby3, in which mRuby3 was tagged endogenously at the C-terminal of Sns (PMID: 39195240 and PMID: 39431457), to show the slit diaphragm pattern.

      Reviewer #2 (Public Review):

      Summary:

      In their manuscript, Zhao et al. describe a link between JAK-STAT pathway activation in nephrocytes on a high-fat diet. Nephrocytes are the homologs to mammalian podocytes and it has been previously shown, that metabolic syndrome and obesity are associated with worse outcomes for chronic kidney disease. A study from 2021 (Lubojemska et al.) could already confirm a severe nephrocyte phenotype upon feeding Drosophila a high-fat diet and also linking lipid overflow by expressing adipose triglyceride lipase in the fat body to nephrocyte dysfunction. In this study, the authors identified a second pathway and mechanism, how lipid dysregulation impact on nephrocyte function. In detail, they show activation of JAK-STAT signaling in nephrocytes upon feeding them a high-fat diet, which was induced by Upd2 expression (a leptin-like hormone) in the fat body, and the adipose tissue in Drosophila. Further, they could show genetic and pharmacological interventions can reduce JAK-STAT activation and thereby prevent the nephrocyte phenotype in the high-fat diet model.

      Strengths:

      The strength of this study is the combination of genetic tools and pharmacological intervention to confirm a mechanistic link between the fat body/adipose tissue and nephrocytes. Inter-organ communication is crucial in the development of several diseases, but the underlying mechanisms are only poorly understood. Using Drosophila, it is possible to investigate several players of one pathway, here JAK-STAT. This was done, by investigating the functional role of Hop, Socs36E, and Stat92E in nephrocytes and has also been combined with feeding a high-fat diet, to assess restoration of nephrocyte function by inhibiting JAK-STAT signaling. Adding a translational approach was done by inhibiting JAK-STAT signaling with methotrexate, which also resulted in attenuated nephrocyte dysfunction. Expression of the leptin-like hormone upd2 in the fat body is a good approach to studying inter-organ communication and the impact of other organs/tissue on nephrocyte function and expands their findings from nephrocyte function towards whole animal physiology.

      Weaknesses:

      Although the general findings of this study are of great interest, there are some weaknesses in the study, which should be addressed. Overall, the number of flies investigated for the majority of the experiments is very low (6 flies) and it is not clear whether the flies used, are from independent experiments to exclude problems with food/diet. For the analysis, the mean values of flies should be calculated, as one fly can be considered a biological replicate, but not all individual cells. By increasing the number of flies investigated, statistical analysis will become more solid. In addition, the morphological assessment is rather preliminary, by only using a Pyd antibody. Duf or Sns should be visualized as well, also the investigation of the different transgenic fly strains studying the importance of JAK-STAT signaling in nephrocytes needs to include a morphological assessment. Moreover, the expected effect of feeding a high-fat diet on nephrocytes needs to be shown (e.g. by lipid droplet formation) and whether upd2 is actually increased here should also be assessed. The time points of assessment vary between 1, 3, and 7 days and should be consistent throughout the study or the authors should describe why they use different time points.

      We thank the reviewer for the comments and suggestions. HFD causes enlarged crop (Liao et al, 2021, PMID: 33171202) and accumulation of lipid droplets in the intestine. To exclude the problems with different batches of food/diet, we checked crop and the intestine during the sample preparation as indications of food consistency.

      We followed the suggestion to take the mean values of flies in the data analysis, one was considered a biological replicate in the revised version. We added in another slit diaphragm protein reporter Sns-mRuby3, in which mRuby3 fluorescent protein was tagged at the C-terminal of endogenous Sns. This reporter was used to show the effect of HFD on slit diaphragm protein, manipulation of Jak/Stat pathway (ppl-Gal4>upd2 and dot-Gal4>UAS-Stat92E-RNAi), and drug treatment.

      Lubojemska et al 2021 (PMID: 33945525) showed that HFD leads to lipid droplet accumulation in larval nephrocytes. Following the reviewer’s suggestion, we stained the adult nephrocytes with Nile red and found lipid droplet formation caused by HFD, verifying the HFD effects on lipid droplet accumulation.

      Regarding the timepoints, the newly eclosed flies (1-day old) were treated for 7 days (transferred to fresh diet or shifted from 18 to 29 °C for 7 days to induce target gene expression). Thus, the flies were 7 days old. In the revised manuscript, we changed “1-day-old females” to “7-day-old females” in the figure legend. The exception was Figure 4 panel G and H, we used Day 3 for the UAS-hop.Tum overexpression in the flp-out clones, which is different from the HFD approach (Day 7). This is because Hop.Tum is a strong gain of function mutation. UAS-hop.Tum overexpression in the eye imaginal disc leads to apoptosis via up-regulating a proapoptotic gene hid (Bhawana Maurya et al, 2021, PMID: 33824299). Thus, we used Day 3 for this experiment.

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      There are relevant issues, that should be addressed:

      Major:

      - The analysis of JAK/STAT signaling in nephrocytes is limited to nephrocyte function, despite the nice slit diaphragm phenotype shown in Figure 2A. What happens to the slit diaphragm in the other genotypes, the rescue settings in particular? Immunofluorescence of Pyd should be explored for all conditions to evaluate proper phenocopy. Tracer endocytosis is much less specific.

      We thank the reviewer for the suggestion. We made a transgenic line Sns-mRuby3, in which mRuby3 was tagged to the endogenous Sns C-terminal. It has been used as a slit diaphragm reporter (PMID: 39195240 and PMID: 39431457). Apart from the tracer assays, we used Sns-mRuby3 reporter and/or Pyd staining to visualize the changes in slit-diaphragm structures.

      - The interventions are restricted to single RNAi lines and reporters, raising concerns about specificity/potential off-targets. Additional lines should be tested for verification.

      Different versions of RNAi lines are available for targeting fly genes. For UAS-Socs36E-RNAi, we chose the one that was generated with a short hairpin, which is known to restrict the off-target effects (Ni et al, 2011, PMID: 21460824). For UAS-Stat92E-RNAi, we added in an independent RNAi line (Figure 6 - figure supplement 1 and 2).   

      Minor:

      - In Figure 2C, the image of HFD shows a section that cuts through the surface at a shallower angle, making everything appear blurry. This image should be replaced.

      We replaced Figure 2C (the image of HFD) with another one.

      - What is the relevance (if any) of reduced electrodense vacuoles with a high-fat diet? An effect on endocytic trafficking/endosome architecture remains unexplored.

      Lubojemska et al (PMID: 33945525) studied the endocytic trafficking/endosome architecture of the larval nephrocytes and found that HFD impaired the endocytosis. We studied the adult pericardial nephrocytes. It is very likely that the endocytic trafficking/endosome architecture is affected by HFD in the adult nephrocytes.  

      - How do the findings presented in this manuscript correlate with a similar study by Lubojemska et al.? At least the discussion should provide more evaluation of this aspect.

      Lubojemska et al (PMID: 33945525) assayed the larval nephrocytes and found that a HFD leads to the ectopic accumulation of lipid droplets in the nephrocytes and decreased endocytosis. They further demonstrated that lipid droplet lipolysis and PGC1α counteracts the harmful effects of a HFD. We performed Nile red staining and verified the accumulation of lipid droplets in the adult pericardial nephrocytes upon HFD feeding, which agrees with Lubojemska discovery. We found that a HFD activates Jak/Stat pathway, which mediates the nephrocyte functional defects. A previous study showed that Stat1 has an inhibitory effect on PGC1α transcription (PMID: 26689548). Further study is needed to investigate the interaction between Jak/Stat pathway and PGC1α transcription. We added the information to the discussion.

      - Please check spelling and grammar.

      Reviewer #2 (Recommendations For The Authors):

      (1) Which cells are investigated? Please state.

      Pericardial nephrocytes were used in this study. The information was added to the result parts.

      (2) Rephrase 'chronic kidney disease model'. Feeding for 7 days and assessment after 7 days cannot be considered chronic as flies can live more than 60 days.

      Lubojemska et al (PMID: 33945525) fed the newly hatched larvae with a HFD and used the third instar larvae for the experiments. The term “chronic kidney disease” has been used in the reference PMID: 33945525. It takes about 4 days for fly larvae to develop from the first instar to the third instar. Thus, the animals were fed on the HFD for only 4 days. In this regard, feeding for seven days might be considered as chronic.

      (3) Line 89: Curran et al., 2014). with risk increasing risk as BMI increases (Hsu et al., 2006). Please correct this sentence.

      We thank the reviewer for finding the error. In the revised version, the sentence was changed as “with increasing risk as BMI increases (Hsu et al., 2006)”.

      (4) Figure 1: The authors should explain why they use FITC-Albumin and 10kDA dextran, what are the differences, and why are both used?

      The tracers are different in size (70kD FITC-Albumin and 10kDA dextran). Both FITC-Albumin and 10kDA dextran have been used in previous publications (Zhao et al 2024, PMID: 39431457 and Weavers et al 2009, PMID: 18971929) to show that the nephrocytes can efficiently take up the tracers of different sizes.

      (5) Figure 3: The JAK-STAT sensor was used on Day 1 to confirm activation of JAKSTAT signaling, which means a very fast response towards the HFD after 24hrs. How is the activation after 7 days? The nephrocyte assessment in Figures 1 and 2 is done at the later time point, how about earlier time points in HFD? One would expect an earlier phenotype as well if JAK-STAT signaling is causative.

      In Figure 3C, newly eclosed flies (1-day old) were fed on a control diet or a HFD for 7 days. Thus, in the legend it shall be “7-day-old females”. Sorry for misleading. The caption was updated as “7-day-old females”.

      (6) Figure 4H: I don't understand how many cells or flies are depicted and analysed? Are the dots one nephrocyte from 4 flies? If yes, the numbers need to be increased.

      In figure 4H, we quantified 5 UAS-hop.Tum clones and 5 neighbor cells. We only found 5 clones from 4 flies. We didn’t quantify all the nephrocytes, since we compared the clone with its neighbor cell. To make it easier to follow, we changed the description as “n= 5 clones and 5 neighbor cells”.

      (7) Figure 4: Why are flies investigated at different ages? Day 1 vs Day 3? This should be consistent with the HFD approach and day 7. Or investigate the HFD at earlier time points as well.

      In Figure 4, the newly eclosed flies (1-day old) were shifted from 18 to 29 °C for 7 days to induce target gene expression. Thus, the flies were 7-day old. In the revised manuscript, we changed “1-day-old females” to “7-day-old females” in the figure legend. We used Day 3 for the UAS-hop.Tum overexpression in the flp-out clones, which is different from the HFD approach (Day 7). This is because Hop.Tum is a strong gain of function mutation. UAS-hop.Tum overexpression in the eye imaginal disc leads to apoptosis via up-regulating a proapoptotic gene hid (Bhawana Maurya et al, 2021, PMID: 33824299). Thus, we used Day 3 for this experiment.

      (8) Figure 5: Do the authors see upd2-GFP in the nephrocyte or at the nephrocyte? Is upd2 filtered to bind the JAK-STAT-receptor? They should show this, which is easy to do due to the GFP label.

      We thank the reviewer for the suggestion. We looked into the nephrocyte from ppl-Gal4>upd2-GFP flies and found Upd2-GFP in the nephrocytes. We further showed that ppl-Gal4 was not expressed in the nephrocytes, suggesting that Upd2-GFP is secreted from the fat body and transported to the nephrocytes. We stained the nephrocytes for Pyd and found compromised fingerprint pattern caused by Upd2-GFP expression in the fat body. The data was added to Figure 5 - figure supplement 1.

      (9) Figure 5: What are the upd2 levels after day 1 and compared to HFD at day 7? In the Rajan et al manuscript, upd2 levels have been assessed by qPCR, this can be done here as well. Although there is a mechanistic link shown here, I think it would be interesting to test the upd2 levels at the different time points assessed.

      In the Rajan et al manuscript, they showed that the expression of upd2 was up regulated by HFD. My previous work showed that HFD changes taste perception. We performed qPCR to determine the expression of upd2 and verified that upd2 was upregulated in HFD fed flies (Yunpo Zhao et al. 2023. PMID: 37934669). We included the reference in the revised version.

      (10) Figure 6: Does a Socs36E overexpression e.g. with the Bloomington strain 91352 also rescue the HFD phenotype, by blocking JAK-STAT signaling?

      We thank the reviewer for the suggestion. We tested the effect of Socs36E overexpression and observed that UAS-Socs36E can partially rescue HFD caused nephrocyte functional decline. The data was not included in the revised manuscript. Notably, apart from having an inhibitory effect on the Jak/Stat, Socs36E represses MAPK pathway (Amoyel et al, 2016, PMID: 26807580).    

      (11) Figure 7: What is the control for the methotrexate treatment? What is the solvent?

      We used DMSO as the solvent for methotrexate and used it as the control for the methotrexate treatment. We added the following sentences to the method parts, “Methotrexate (06563, Sigma-Aldrich, MO) was dissolved in DMSO to make a 10mM stock solution”, and “The samples incubated in Schneider’s Medium supplemented with DMSO vehicle were used a control”.

      (12) Why did the authors use Dot-Gal4 for the Socs36E knockdown and Dot-Gal4ts for the Stat92E knockdown?

      We used Dot-Gal4ts and temperature shifting to restrict the Stat92E knockdown at adult stages.

      (13) Supplementary Figure 1: Please add the individual data to the figure as done for all other figures.

      We thank the reviewer for this comment. The figure individual data was added according to the suggestion.

    1. Author response:

      The following is the authors’ response to the original reviews

      Public Reviews:

      Reviewer #1 (Public review):

      Summary

      The authors use microscopy experiments to track the gliding motion of filaments of the cyanobacteria Fluctiforma draycotensis. They find that filament motion consists of back-and-forth trajectories along a "track", interspersed with reversals of movement direction, with no clear dependence between filament speed and length. It is also observed that longer filaments can buckle and form plectonemes. A computational model is used to rationalise these findings.

      We thank the reviewer for this accurate summary of the presented work.

      Strengths:

      Much work in this field focuses on molecular mechanisms of motility; by tracking filament dynamics this work helps to connect molecular mechanisms to environmentally and industrially relevant ecological behavior such as aggregate formation.

      The observation that filaments move on tracks is interesting and potentially ecologically significant.

      The observation of rotating membrane-bound protein complexes and tubular arrangement of slime around the filament provides important clues to the mechanism of motion.

      The observation that long filaments buckle has the potential to shed light on the nature of mechanical forces in the filaments, e.g. through the study of the length dependence of buckling.

      We thank the reviewer for listing these positive aspects of the presented work.

      Weaknesses:

      The manuscript makes the interesting statement that the distribution of speed vs filament length is uniform, which would constrain the possibilities for mechanical coupling between the filaments. However, Figure 1C does not show a uniform distribution but rather an apparent lack of correlation between speed and filament length, while Figure S3 shows a dependence that is clearly increasing with filament length. Also, although it is claimed that the computational model reproduces the key features of the experiments, no data is shown for the dependence of speed on filament length in the computational model. The statement that is made about the model "all or most cells contribute to propulsive force generation, as seen from a uniform distribution of mean speed across different filament lengths", seems to be contradictory, since if each cell contributes to the force one might expect that speed would increase with filament length.

      We agree that the data shows in general a lack of correlation, rather than strictly being uniform. In the revised manuscript, we intend to collect more data from observations on glass to better understand the relation between filament length and speed.

      In considering longer filaments, one also needs to consider the increased drag created by each additional cell - in other words, overall friction will either increase or be constant as filament length increases. Therefore, if only one cell (or few cells) are generating motility forces, then adding more cells in longer filaments would decrease speed.

      Since the current data does not show any decrease in speed with increasing filament length, we stand by the argument that the data supports that all (or most) cells in a filament are involved in force generation for motility. We would revise the manuscript to make this point - and our arguments about assuming multiple / most cells in a filament contributing to motility - clear.

      The computational model misses perhaps the most interesting aspect of the experimental results which is the coupling between rotation, slime generation, and motion. While the dependence of synchronization and reversal efficiency on internal model parameters are explored (Figure 2D), these model parameters cannot be connected with biological reality. The model predictions seem somewhat simplistic: that less coupling leads to more erratic reversal and that the number of reversals matches the expected number (which appears to be simply consistent with a filament moving backwards and forwards on a track at constant speed).

      We agree that the coupling between rotation, slime generation and motion is interesting and important when studying the specific mechanism leading to filament motion. However, we believe it is even more fundamental to consider the intercellular coordination that is needed to realise this motion. Individual filaments are a collection of independent cells. This raises the question of how they can coordinate their thrust generation in such a way that the whole filament can both move and reverse direction of motion as a single unit. With the presented model, we want to start addressing precisely this point.

      The model allows us to qualitatively understand the relation between coupling strength and reversals (erratic vs. coordinated motion of the filament). It also provides a hint about the possibility of de-coordination, which we then look for and identify in longer filaments.

      While the model’s results seem obvious in hindsight, the analysis of the model allows phrasing the question of cell-to-cell coordination, which so far has not been brought up when considering the inherently multi-cell process of filament motility.

      Filament buckling is not analysed in quantitative detail, which seems to be a missed opportunity to connect with the computational model, eg by predicting the length dependence of buckling.

      Please note that Figure S10 provides an analysis of filament length and number of buckling instances observed. This suggests that buckling happens only in filaments above a certain length.

      We do agree that further analyses of buckling - both experimentally and through modelling would be interesting. This study, however, focussed on cell-to-cell coupling / coordination during filament motility. We have identified the possibility of de-coordination through the use of a simple 1D model of motion, and found evidence of such de-coordination in experiments. Notice that the buckling we report does not depend on the filament hitting an external object. It is a direct result of a filament activity which, in this context, serves as evidence of cellular de-coordination.

      Now that we have observed buckling and plectoneme formation, these processes need to be analysed with additional experiments and modelling. The appropriate model for this process needs to be 3D, and should ideally include torques arising from filament rotation. Experimentally, we need to identify means of influencing filament length and motion and see if we can measure buckling frequency and position across different filament lengths. These works are ongoing and will have to be summarised in a separate, future publication.

      Reviewer #2 (Public review):

      Summary:

      The authors combined time-lapse microscopy with biophysical modeling to study the mechanisms and timescales of gliding and reversals in filamentous cyanobacterium Fluctiforma draycotensis. They observed the highly coordinated behavior of protein complexes moving in a helical fashion on cells' surfaces and along individual filaments as well as their de-coordination, which induces buckling in long filaments.

      We thank the reviewer for this accurate summary of the presented work.

      Strengths:

      The authors provided concrete experimental evidence of cellular coordination and de-coordination of motility between cells along individual filaments. The evidence is comprised of individual trajectories of filaments that glide and reverse on surfaces as well as the helical trajectories of membrane-bound protein complexes that move on individual filaments and are implicated in generating propulsive forces.

      We thank the reviewer for listing these positive aspects of the presented work.

      Limitations:

      The biophysical model is one-dimensional and thus does not capture the buckling observed in long filaments. I expect that the buckling contains useful information since it reflects the competition between bending rigidity, the speed at which cell synchronization occurs, and the strength of the propulsion forces.

      Cell-to-cell coordination is a more fundamental phenomenon than the buckling and twisting of longer filaments, in that the latter is a consequence of limits of the former. In this sense, we are focussing here on something that we think is the necessary first step to understand filament gliding. The 3D motion of filaments (bending, plectoneme formation) is fascinating and can have important consequences for collective behaviour and macroscopic structure formation. As a consequence of cellular coupling, however, it is beyond the scope of the present paper.

      Please also see our response above. We believe that the detailed analysis of buckling and plectoneme formation requires (and merits) dedicated experiments and modelling which go beyond the focus of the current study (on cellular coordination) and will constitute a separate analysis that stands on its own. We are currently working in that direction.

      Future directions:

      The study highlights the need to identify molecular and mechanical signaling pathways of cellular coordination. In analogy to the many works on the mechanisms and functions of multi-ciliary coordination, elucidating coordination in cyanobacteria may reveal a variety of dynamic strategies in different filamentous cyanobacteria.

      We thank the reviewer for highlighting this point again and seeing the value in combining molecular and dynamical approaches.

      Reviewer #3 (Public review):

      Summary:

      The authors present new observations related to the gliding motility of the multicellular filamentous cyanobacteria Fluctiforma draycotensis. The bacteria move forward by rotating their about their long axis, which causes points on the cell surface to move along helical paths. As filaments glide forward they form visible tracks. Filaments preferentially move within the tracks. The authors devise a simple model in which each cell in a filament exerts a force that either pushes forward or backwards. Mechanical interactions between cells cause neighboring cells to align the forces they exert. The model qualitatively reproduces the tendency of filaments to move in a concerted direction and reverse at the end of tracks.

      We thank the reviewer for this accurate summary of the presented work.

      Strengths:

      The observations of the helical motion of the filament are compelling. The biophysical model used to describe cell-cell coordination of locomotion is clear and reasonable. The qualitative consistency between theory and observation suggests that this model captures some essential qualities of the true system.

      The authors suggest that molecular studies should be directly coupled to the analysis and modeling of motion. I agree.

      We thank the reviewer for listing these positive aspects of the presented work and highlighting the need for combining molecular and biophysical approaches.

      Weaknesses:

      There is very little quantitative comparison between theory and experiment. It seems plausible that mechanisms other than mechano-sensing could lead to equations similar to those in the proposed model. As there is no comparison of model parameters to measurements or similar experiments, it is not certain that the mechanisms proposed here are an accurate description of reality. Rather the model appears to be a promising hypothesis.

      We agree with the referee that the model we put forward is one of several possible. We note, however, that the assumption of mechanosensing by each cell - as done in this model - results in capturing both the alignment of cells within a filament (with some flexibility) and reversal dynamics. We have explored an even more minimal 1D model, where the cell’s direction of force generation is treated as an Ising-like spin and coupled between nearest neighbours (without assuming any specific physico-chemical basis). We found that this model was not fully able to capture both phenomena. In that model, we found that alignment required high levels of coupling (which is hard to justify except for mechanical coupling) and reversals were not readily explainable (and required additional assumptions). These points led us to the current, mechanically motivated model.

      The parameterisation of the current model would require measuring cellular forces. To this end, a recent study has attempted to measure some of the physical parameters in a different filamentous cyanobacteria [1] and in our revision we will re-evaluate model parameters and dynamics in light of that study. We will also attempt to directly verify the presence of mechano-sensing by obstructing the movement of filaments.

      Summary from the Reviewing Editor:

      The authors present a simple one-dimensional biophysical model to describe the gliding motion and the observed statistics of trajectory reversals. However, the model does not capture some important experimental findings, such as the buckling occurring in long filaments, and the coupling between rotation, slime generation, and motion. More effort is recommended to integrate the information gathered on these different aspects to provide a more unified understanding of filament motility. In particular, the referees suggest performing a more quantitative analysis of the buckling in long filaments. Finally, it is also recommended to discuss the results in the context of previous literature, in order to better explain their relevance. Please find below the detailed individual recommendations of the three reviewers.

      We thank the editor for this accurate summary of the presented work and for highlighting the key points raised by the reviewers. We have provided below point-by-point replies to these.

      Recommendations for the authors:

      Reviewer #1 (Recommendations for the authors):

      The relevance of the study organism Fluctiforma draycotensis is not clearly explained, and the results are not discussed in the context of previous literature. The motivation would be clearer if the manuscript explained why this model organism was chosen and how the results compare with those previously observed for this or other organisms.

      We have extended the introduction and discussion sections to make it clearer why we have worked with this organism and how the findings from this work relate to previous ones. In brief, Flucitforma draycotensis is a useful organism to work with as it not only displays significant motility but it also displays intriguing collective behaviour at different scales. Previous works on gliding motility in filamentous cyanobacteria have mostly focussed on the model organism Nostoc punctiforme, which only displays motility after differentiation into hormogonia [1]. There have also been studies in a range of different filamentous species, including those of the non-monophyletic genus, Phormidium, but these studies mostly looked at effects of genetic deletions on motility [2] or utilised electron microscopy to identify proteins (or surface features) involved in motility [3-5]. It must be noted that motility is also described and studied in non-filamentous cyanobacteria, but the dynamics of motion and molecular mechanisms there are different to filamentous cyanobacteria [6,7]. These previous studies are now cited / summarised in the revised introduction and discussion sections.

      The inferred tracks, probably associated with secreted slime, play a key role since it is supposed that the tracks provide the external force that keeps the filaments straight. Movie S3, in phase contrast, provides convincing evidence for the tracks, but they cannot be seen in the fluorescence images presented in the main text. Clearer evidence of them should be shown in the main text. An especially important aspect of the tracks is where they start and end since the computational model assumes that reversal happens due to forces generated by reaching the end of a track. Therefore it seems important to comment on what produces the tracks, to check whether reversals actually happen at the end of a track, etc. Perhaps tracks could be strained with Concanavalin-A?

      To confirm that reversals happen on track ends, we have now performed an analysis on agar, where we can see tracks on phase microscopy. This analysis confirms that, on agar, reversals indeed happen on track ends. We added this analysis, along with images showing tracks clearly as a new Fig in the main text (see new Fig. 1).

      Further confirming the reversal at track ends, we note that filaments on circular tracks do not not reverse over durations longer than the ‘expected reversal interval’ of a filament on a straight track (see details in response to Reviewer 2).

      Regarding what produces the tracks on agar, we are still analysing this using different methods and these results will be part of a future study. Fluorescent staining can be used to visualise slime tubes using TIRF microscopy, as shown in Fig. S8, however, visualising tracks on agar using low magnification microscopy has been difficult due to background fluorescence from agar.

      We would also like to clarify that the model does not incorporate any assumptions regarding the track-filament interaction, other than that the track ends behave akin to a physical boundary for the filament. The observed reversal at track ends and “what” produces the track are distinct aspects of filament motion. We do not think that the model’s assumption of filament reversal at the end of the track requires understanding of the mechanism of slime production.

      Reviewer #3 (Recommendations for the authors):

      The manuscript combines three distinct topics: (1) the difference in locomotion on glass vs agar, (2) the development of a biophysical model, and (3) the helical motion of filament. It is not clear what insight one can gain from any one of these topics about the two others. The manuscript would be strengthened by more clearly connecting these three aspects of the work. A stronger comparison of theory to observation would be very useful. Some suggestions:

      (1) The observation that it is only the longest filaments that buckle is interesting. It should be possible to predict the critical length from the biophysical model. Doing so could allow fits of some model parameters.

      (2) What model parameters change between glass and agar? Can you explain these qualitative differences in motility by changing one model parameter?

      (3) Is it possible to exert a force on one end of a filament to see if it is really mechano-sensing that couples their motion?

      We thank the reviewer for this comment and agree with them that a better connection between model and experiment should be sought. We believe that the new analyses, presented below in response to the 2nd suggestion of the reviewer, provide such a connection in the context of reversal frequency. As stated below, we think that the 1st suggestion falls outside of the scope of the current work, but should form the basis of a future study.

      Regarding suggestion (1) - addressing buckling:

      We agree with the reviewer that using a model to predict a critical buckling length would be useful. We note, however, that the presented study focussed on cell-to-cell coupling / coordination during filament motility using a 1D, beadchain model. The buckling observations served, in this context, as evidence of cellular de-coordination. Now that we have observed buckling (and plectoneme formation), these processes need to be analysed with further experiments and modelling. The appropriate model for studying buckling would have to be at least 2D (ideally 3D) and consider elastic forces and torques relating to filament bending, rotation, and twisting. Experimentally, we need to identify means of influencing filament length and motion and undertake further measurements of buckling frequency and position across different filament lengths. These investigations are ongoing and will be summarised in a separate, future publication.

      Regarding suggestion (2) - addressing differences in motility on agar vs. glass:

      We believe that the two key differences between agar and glass experiments are the occasional detachment of filaments from substrate on glass and the lack of confining tracks on glass. These differences might arise from the interactions between the filament, the slime, and the surface. As both slime and agar contain polysaccharides, the slime-agar interaction can be expected to be different from the slime-glass interaction. Additionally, in the agar experiments, the filaments are confined between the agar and a glass slide, while they are not confined on the glass, leaving them free to lift up from the glass surface. We expect these factors to alter reversal frequency between the two conditions. To explore this possibility, we have now extended the analysis of experimental data from glass and present that (see details below):

      (i) dwell times are similar between agar and glass, and

      (ii) reversal frequency distribution is different between glass and agar, and remains constant across filament length on glass.

      We were able to explore these experimental findings with new model simulations, by removing the assumption of an “external bounding frame”. We then analysed reversal frequency within against model parameters, as detailed below.

      “The movement of the filaments on glass. We have extended our analysis of motility on glass resulting in the following noted features. Firstly, the median speed shows a weak positive correlation with filament length on glass (see original Fig S3B vs. updated Fig. S3A). This is slightly different to agar, where we do not observe any strong correlation in either direction (see original, Fig. 1 vs. updated Fig 2). Both the cases of positive, and no correlation, support our original hypothesis that the propulsion force is generated by multiple cells within the filament.

      Secondly, the filaments on glass display ‘stopping’ events that are not followed by a reversal, but are instead followed by a continuation in the original direction of motion, which we term ‘stop-go’ events, in contrast to the reversals. The dwell times associated with reversals and ‘stop-go’ events are similarly distributed (see original Fig S3A vs. updated Fig S3B). Furthermore, the dwell time distributions are similar between agar and glass (compare old Fig. 1C vs. new Fig 2C and new Fig. S3B). This suggests that the reversal process is the same on both agar and glass.

      Thirdly, we find that the frequencies of both reversal and stop-go events on glass are uncorrelated with the filament length (see new Fig. S4A) and there are approximately twice as many reversals as stop-go events. In contrast, the filaments on agar reverse with a frequency that is inversely proportional to the filament length (which is in turn proportional to the track length) (see original Fig. S1). The distribution of reversal frequencies on agar is broader and flatter than the distribution on glass (see new Fig. S4B). These findings are inline with the idea that tracks on agar (which are defined by filament length) dictate reversal frequency, resulting in the strong correlations we observe between reversal frequency, track length, and filament length. On glass, filament movement is not constrained by tracks, and we have a specific reversal frequency independent of filament length.”

      “Model can capture movement of filaments on glass and provides hypotheses regarding constancy of reversal frequency with length. We believe the model parameters controlling cellular memory (ω<sub>max</sub>) and strength of cellular coupling (K<sub>ω</sub>) describe the internal behaviour of a filament and therefore should not change depending on the substrate. Thus, we expect the model to be able to capture movement on glass just by removal of any ‘confining tracks’, i.e external forces, from the simulations. Indeed, we find that the model displays both stop-go and reversal events when simulated without any external force and can capture the dwell time distribution under this condition (compare new Figs. S12,S13 with S3).

      In terms of reversal frequency, however, the model shows a reduction in reversal frequency with filament length (see new Fig. S15). This is in contrast to the experimental data. We find, however, that model results also show a reduction in reversal frequency with increasing (ω<sub>max</sub> and K<sub>ω</sub> (see new Fig. S14 and S15). This effect is stronger with (ω<sub>max</sub>, while it quickly saturates with K<sub>ω</sub> (see new Fig. S14). Therefore, one possibility of reconciling the model and experiment results in terms of constant reversal frequency with filament length would be to assume that (ω<sub>max</sub> is decreasing with filament length (see new Fig. S16). Testing this hypothesis - or adding additional mechanisms into the model - will constitute the basis of future studies.”

      Regarding suggestion (3) - role of mechanosensing:

      We have tried several experiments to evaluate mechanosensing. First, we have used a micropipette or a thin wire placed on the agar, to create a physical barrier in the way of the filaments. The micropipette approach was not quite feasible in our current setup. The wire approach was possible to implement, but the wire caused a significant undulation / perturbation on agar. Possibly relating to this, filaments tended to continue moving alongside the wire barrier. Therefore, these experiments were inconclusive at this stage with regards to mechanosensing a physical barrier. As an alternative, we have attempted trapping gliding filaments using an optical trap with a far red laser that should not affect the physiology of the cells. This did not cause an immediate reversal in filament motion. However, this could be due to the optical trap strength being below the threshold value for mechanosensing. The force per unit length generated by filamentous cyanobacteria has been calculated via a model of self-buckling rods, giving a value of ≈1nN/μm [8]. In comparison, the optical trap generates forces on the scale of pN. Thus, the trap force is several orders of magnitude lower than the propulsive force generated by a filament, given filament lengths in the range of ten to several hundreds μm. We conclude that the lack of observed response may be due to the optical trap force being too weak.

      Thus, the experiments we can perform using our current available methods and equipment are not able to prove either the presence or the absence of mechanosensing in the filament. We plan to perform further experiments in this direction, involving new and/or improved experimental setups, such as use of Atomic Force Microscopy.

      We would like to note that there is an additional observation that supports the idea of reversals being mediated by mechanosensing at the end of a track, instead of the locations of the track ends being caused by the intrinsic reversal frequency of the filament. In a few instances (N = 4), filaments on agar ended up on a circular track (see Movie S4 for an example). These filaments did not reverse over durations a few times longer than the ‘expected reversal interval’ of a filament on a straight track.

      Should $N$ following eq 7 and in eq 9 be $N_f$?

      We have corrected this typo.

      It would be useful to include references to what is known about mechanosensing in cyanobacteria.

      We agree with the reviewer, and we have not updated the discussion section to include this information. Mechanosensing has not yet been shown directly in any cyanobacteria, but several species are shown to harbor genes that are implicated (by homology) to be involved in mechanosensing. In particular, analysis of cyanobacterial genomes predicts the presence of a significant number of homologues of the Escherichia coli mechanosensory ion channels MscS and MscL [9]. We have also identified similar MscS protein sequences in F. draycotensis. These channels open when the membrane tension increases, allowing the cell to protect itself from swelling and rupturing when subject to extreme osmotic shock. [10,11]

      We also note that F. draycotensis, as with other filamentous cyanobacteria, have genes associated with the type IV pili, which may be involved in the surface-based motility [1]. Type IV pili have been shown to be mechanosensitive. For example, in cells of Pseudomonas aeruginosa that ‘twitch’ on a surface using type IV pili, application of mechanical shear stress results in increased production of an intracellular signalling molecule involved in promoting biofilm production. The pilus retraction motor has been shown to be involved in this shear-sensing response [12]. Additionally, twitching P. aeruginosa cells often reverse in response to collisions with other cells. Reversal is also caused by collisions with inert glass microfibres, which suggests that the pili-based motility can be affected by a mechanical stimulus [13].

      References

      (1) D. D. Risser, Hormogonium Development and Motility in Filamentous Cyanobacteria. Appl Environ Microbiol 89, e0039223 (2023).

      (2) T. Lamparter et al., The involvement of type IV pili and the phytochrome CphA in gliding motility, lateral motility and photophobotaxis of the cyanobacterium Phormidium lacuna. PLoS One 17, e0249509 (2022)

      (3) E. Hoiczyk, Gliding motility in cyanobacteria: observations and possible explanations. Arch Microbiol 174, 11-17 (2000).

      (4) D. G. Adams, D. Ashworth, B. Nelmes, Fibrillar Array in the Cell Wall of a Gliding Filamentous Cyanobacterium. Journal of Bacteriology 181 (1999).

      (5) L. N. Halfen, R. W. Castenholz, Gliding in a blue-green alga: a possible mechanism. Nature 225, 1163-1165 (1970).

      (6) S. N. Menon, P. Varuni, F. Bunbury, D. Bhaya, G. I. Menon, Phototaxis in Cyanobacteria: From Mutants to Models of Collective Behavior. mBio 12, e0239821 (2021).

      (7) F. D. Conradi, C. W. Mullineaux, A. Wilde, The Role of the Cyanobacterial Type IV Pilus Machinery in Finding and Maintaining a Favourable Environment. Life (Basel) 10 (2020).

      (8) M. Kurjahn, A. Deka, A. Girot, L. Abbaspour, S. Klumpp, M. Lorenz, O. Bäumchen, S. Karpitschka Quantifying gliding forces of filamentous cyanobacteria by self-buckling. eLife 12:RP87450 (2024).

      (9) S.C. Johnson, J. Veres, H. R. Malcolm, Exploring the diversity of mechanosensitive channels in bacterial genomes. Eur Biophys J 50, 25–36 (2021).

      (10) S.I. Sukharev, W.J. Sigurdson, C. Kung, F. Sachs, Energetic and spatial parameters for gating of the bacterial large conductance mechanosensitive channel, MscL. Journal of General Physiology, 113(4), 525-540 (1999).

      (11) N. Levina, S. Tötemeyer, N.R. Stoke, P. Louis, M.A. Jones, I.R. Boot. Protection of Escherichia coli cells against extreme turgor by activation of MscS and MscL mechanosensitive channels: identification of genes required for MscS activity. The EMBO journal (1999).

      (12) V.D. Gordon, L. Wang, Bacterial mechanosensing: the force will be with you, always. Journal of cell science 132(7):jcs227694 (2019).

      (13) M.J. Kühn, L. Talà, Y.F. Inclan, R. Patino, X. Pierrat, I. Vos, Z. Al-Mayyah, H. Macmillan, J. Negrete Jr, J.N. Engel, A. Persat, Mechanotaxis directs Pseudomonas aeruginosa twitching motility. Proceedings of the National Academy of Sciences. 118(30):e2101759118 (2021).

    1. Reviewer #3 (Public review):

      Summary:

      After salamander limb amputation, the cross-section of the stump has two major axes: anterior-posterior and dorsal-ventral. Cells from all axial positions (anterior, posterior, dorsal, ventral) are necessary for regeneration, yet the molecular basis for this requirement has remained unknown. To address this gap, Yamamoto et al. took advantage of the ALM assay, in which defined positional identities can be combined on demand and their effects assessed through the outgrowth of an ectopic limb. They propose a compelling model in which dorsal and ventral cells communicate by secreting Wnt10b and Fgf2 ligands, respectively, with this interaction inducing Shh expression in posterior cells. Shh was previously shown to induce limb outgrowth in collaboration with anterior Fgf8 (PMID: 27120163). Thus, this study completes a concept in which four secreted signals from four axial positions interact for limb patterning. Notably, this work firmly places dorsal-ventral interactions upstream of anterior-posterior, which is striking for a field that has been focussed on anterior-posterior communication. The ligands identified (Wnt10b, Fgf2) are different from those implicated in dorsal-ventral patterning in the non-regenerative mouse and chick models. The results in the context of ALM/ectopic limb engineering are impressive, but the authors do not extend their experiments to assay 'normal' regeneration after amputation.

      Strengths:

      (1) The ALM and use of GFP grafts for lineage tracing (Figures 1-3) take full advantage of the salamander model's unique ability to outgrow patterned limbs under defined conditions. As far as I am aware, the ALM has not been combined with precise grafts that assay 2 axial positions at once, as performed in Figure 3. The number of ALMs performed in this study deserves special mention, considering the challenging surgery involved.

      (2) The authors identify that posterior Shh is not expressed unless both dorsal and ventral cells are present. This echoes previous work in mouse limb development models (AER/ectoderm-mesoderm interaction), but this link between axes was not known in salamanders. The authors elegantly reconstitute dorsal-ventral communication by grafting, finding that this is sufficient to trigger Shh expression (Figure 3 - although see also the Weaknesses section.)

      (3) Impressively, the authors discovered two molecules sufficient to substitute dorsal or ventral cells through electroporation into dorsal- or ventral-depleted ALMs (Figure 5). These molecules did not change the positional identity of target cells. The same group previously identified the ventral factor (Fgf2) to be a nerve-derived factor essential for regeneration. In Figure 6, the authors demonstrate that nerve-derived factors, including Fgf2, are alone sufficient to grow out ectopic limbs from a dorsal wound. Limb induction with a 3-factor cocktail without supplementing with other cells is conceptually important for regenerative engineering.

      (4) The writing style and presentation of results are very clear.

      Weaknesses:

      (1) The expression data are the weakest part of this study.

      • Despite being a central message, I found the Shh in situs unconvincing (e.g. Figure 2I, 3C, 5C), especially without sense probe controls. An additional assay would be essential to make the Shh data convincing - perhaps like in Figure 5D (qPCR?), RNA-sequencing, or a downstream target gene.

      • It is not clear what the n numbers mean for the in situ data (slides analysed / number of biological samples / other?). This is crucial to understanding the reliability of the results.

      • The authors do not assay where and when Wnt10b and Fgf2 are expressed beyond the bulk RNA-sequencing (which presumably contains both epidermis and mesenchyme cells). This is a shame, as understanding which cell types express these molecules, and when, would be important for understanding the mechanism.

      (2) It is important to consider that the ALM is not 'regeneration', even if the authors have previously argued that ALM bumps and regenerating blastemas are equivalent (PMID: 17959163). The start- and end- points of ALM are different from regeneration, even though there are undoubtedly common principles involved. Thus, I find the word 'regeneration' in the title and last sentence of the abstract unsubstantiated unless evidence is provided that the same mechanisms (Wnt10b/Fgf2/Shh) function during normal limb regeneration.

      (3) Drawing the exact boundaries of the Ant/Pos/Dor/Ven BL and grafts in the cartoon in Figure 1 (with respect to anatomical landmarks) would help to better understand the experiments in Figures 3 and 4.

      (4) I find the 'positional cue' and 'positional value' terminology confusing, despite the authors' efforts. It is not clear if they refer to cell autonomous or secreted signals, and, as the authors mention, the definitions partially overlap. Lmx1b is defined as a positional value, even though it is necessary and sufficient for dorsal identity (so, isn't it positional information?). Much simpler would be to describe Wnt10b and Fgf2 as what they are: dorsally or ventrally expressed signals that substitute for dorsal or ventral tissue without inducing changes in positional information.

      Overall appraisal:

      This is a logical and well-executed study that creatively uses the axolotl model to advance an important framework for understanding limb patterning. The reliability of the Shh expression data is a weak point in this otherwise impressive study. The relevance of the mechanisms to normal limb regeneration is not substantiated.

    2. Author response:

      We sincerely thank the editor and all three reviewers for their constructive comments. We deeply appreciate the reviewers’ efforts in highlighting both the strengths and the weaknesses of our study. To enhance the quality and clarity of our work, we plan to address the concerns raised in the public reviews through the following actions:

      (1) Improving the tone and language of the manuscript

      We will revise the manuscript thoroughly, incorporating additional explanations and clarifications where necessary, and improving the tone and language to enhance readability and precision. Especially, we will pay careful attention on the terms “positional information,” “positional value,” and “positional cue,” and we plan to explain them in a historical context.

      (2) Extending analysis to regular blastemas

      To validate the applicability of our proposed model beyond the accessory limb model (ALM), we will examine the gene expression patterns of key signaling molecules in regular blastemas generated by limb amputation. This will allow us to test whether the mechanisms we describe are also active during normal limb regeneration.

      (3) Increasing sample sizes in critical experiments

      In order to ensure reproducibility and statistical reliability, we will increase the number of biological replicates in key experiments within the limitations regulated by our animal ethics approval. Additionally, we will collect data that clearly defines the dorsal/ventral axis within the structures, as far as possible. We will also revise the manuscript to pay closer attention to the anterior/posterior/dorsal/ventral axis in the existing data, ensuring that it is clearly described.

      (4) Adding quantitative gene expression data

      To support and reinforce our in situ hybridization results, we will include additional quantitative gene expression analyses (e.g., qRT-PCR), thereby strengthening the conclusions drawn from our expression data.

      We are grateful for the reviewers’ insights and are confident that these revisions will significantly strengthen our manuscript.

    1. Author response:

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

      We sincerely thank the reviewers for their thoughtful review and feedback. We believe that our work will provide valuable insights into how MRSA evolves under bacteriophage predation and stimulate efforts to use genetic trade-offs to combat drug resistance. We have substantially revised the paper and performed several additional experiments to address the reviewers' questions and concerns.

      Summary:

      (1) Testing for genetic trade-offs in additional S. aureus strains

      We obtained 30 clinical isolates of the S. aureus USA300 strain that were isolated between 2008 and 2011 (see Table S1). We first tested the FStaph1N, Evo2, and FNM1g6 phages against this expanded strain panel and found that Evo2 showed strong activity against all 30 strains (Table S4). We tested whether Evo2 infection could elicit trade-offs in b-lactam resistance for a subset of these strains. We found that Evo2 infection caused a ~10-100-fold reduction in their MIC against oxacillin. This data is now incorporated into a revised Figure 2 in panel C.

      (2) Testing additional staphylococcal phages

      We isolated from the environment a phage called SATA8505. Similar to FStaph1N and Evo2, SATA8505 belongs to the Kayvirus genus and infects the MRSA strains MRSA252, MW2, and LAC. Phage-resistant MRSA recovered following SATA8505 infection also showed a strong reduction in oxacillin resistance (Figure S5). Furthermore, we confirmed that resistance against FNM1g6, which belongs to the Dubowvirus genes, does not elicit tradeoffs in b-lactam resistance (Figure S4). Sequencing analysis of FNM1g6 - resistant LAC strains showed a different mutation fmhC, which was not observed with the FStaph1N and Evo2 phages (Table 1). We have added this new data into the main text and supplemental figures and tables. Future work will focus on obtaining comprehensive analysis of a wide range of phage families. 

      (3) Testing additional antibiotics

      We also expanded our trade-off analysis include wider range of antibiotic classes (Table S3). Overall, the loss of resistance appears to be confined to b-lactams.

      (4) Genetic analysis of ORF141

      In order determine the function of ORF141, which is mutated in Evo2, we attempted to clone wild-type ORF141 into a staphylococcal plasmid and perform complementation assays with Evo2. Unfortunately, obtaining the plasmid-borne wild-type ORF141 has proven to be tricky, as all clones developed frameshift or deletions in the open reading frame. We posit that the gene product of ORF141 is toxic to the bacteria. We are currently working on placing the gene under more stringent expression conditions but feel that these efforts fall outside of the scope of this paper.  

      (5) Testing the effect of single mutants  

      Our genomic analysis showed that phage-resistant MRSA evolved multiple mutations following phage infection, making it difficult to determine the mechanism of each mutation alone. For example, phage-resistant MW2 and LAC evolved nonsense mutations in transcriptional regulators mgrA, arlR, and sarA. To test whether these mutations alone were sufficient to confer resistance, we obtained MRSA strains with single-gene knockouts of mgrA, arlR, and sarA and tested their ability to resist phage. We observed that deletion of mgrA in the MW2 resulted in a modest reduction in phage sensitivity (Figure S7). However, we did not the observe any changes in the other mutant strains. These results suggest that phage resistance in these strains is likely caused by a combination of mutations. Determining the mechanisms of these mutations is the focus if our future work.

      (6) Transcriptomics of phage-resistant MRSA strains

      To further assess the effects of the phage resistance mutations, we performed bulk RNA-seq on phage-resistant MW2 and LAC strains and compared their differential expression levels to the respective wild-type strains. We picked these strains because our genomic data showed that they had evolved mutations in known transcriptional regulators (e.g. mgrA). Our analysis shows that both strains significantly modulate their gene expression (Figure 4). Notably, both strains upregulate the cell wall-associated protein ebh, while downregulating several genes involved in quorum sensing, virulence, and secretion. We have included this new data in Figure 4 and Table S5 and added an entire section in the manuscript discussing these results and their implications.  

      (7) Co-treatment of MRSA with phage and b-lactam

      We performed checkerboard experiments on MRSA strains with phage and b-lactam gradients (Figure 6). We found that under most conditions, MRSA cells were only able to recover under low phage and b-lactam concentrations. Notably, these recovered cells were still phage resistant and b-lactam sensitive. However, under one condition where MW2 was treated with FStaph1N and b-lactam, we found that some recovered cells still had high levels of b-lactam resistance, showing a distinct mutational profile. We discuss these results in detail in the main text.

      Reviewer # 1:

      Strengths:

      Phage-mediated re-sensitization to antibiotics has been reported previously but the underlying mutational analyses have not been described. These studies suggest that phages and antibiotics may target similar pathways in bacteria.

      We thank Reviewer 1 for this assessment. We hope that the data provided in this work will help stimulate further inquiries into this area and help in the development of better phage-based therapies to combat MRSA.

      Weaknesses:

      One limitation is the lack of mechanistic investigations linking particular mutations to the phenotypes reported here. This limits the impact of the work.

      We acknowledge the limitations of our initial analysis. We note (and cite) that separate studies have already linked mutations in femA, mgrA, arlR, and sarA with reduced b-lactam resistance and virulence phenotypes in MRSA, but not to phage resistance. For the other mutations, we could not find literature linking them to our observed phenotypes. We analyzed the effects of single gene knockouts of mgrA, arlR, and sarA on MRSA’s phage resistance. However, as shown above, the results only showed modest effects on phage resistance in the MW2 strain (see Figure S7 and lines 309-317). We therefore believe that mutations in single genes are not sufficient to cause the trade-offs in phage/ b-lactam resistance. Because each MRSA strain evolved multiple mutations (e.g. MW2 evolved 6 or more mutations), we feel that determining the effects of all possible permutations of those mutations was beyond the scope of the paper.

      However, to bridge the mutational data with our phenotypic observations, we performed RNAseq and compared the transcriptomes of un-treated and phage-treated MRSA strains (see Figure 4, Table S5, and lines 337-391). Our results show that phage-treated MRSA strains significantly modulate their transcript levels. Indeed, some of the changes in gene expression can explain for the phenotypic observations (e.g. overexpression of ebh can lead to reduced clumping). Further, the results shown some unexpected patterns, such as the downregulation of quorum sensing genes or genes involved in type VII secretion.

      Another limitation of this work is the use of lab strains and a single pair of phages. However, while incorporation of clinical isolates would increase the translational relevance of this work it is unlikely to change the conclusions.

      We thank the reviewer for this suggestion. We would like to clarify that MW2, MRSA252, and LAC are pathogenic clinical isolates that were isolated between 1997 and 2000’s. However, we acknowledge that, because these 3 strains have been propagated for many generations, they might have acquired laboratory adaptations. We therefore obtained 30 USA300 clinical strains that were isolated in more recent years (~2008-2011) and tested our phages against them. We note that these clinical isolates (generously provided by Dr. Petra Levin’s lab) were preserved with minimal passaging to reduce the effects of laboratory adaptation. We found that the Evo2 phage was able to elicit oxacillin trade-offs in those strains as well. (see Table S1, Table S7, Fig 2C, and lines 210 – 225)

      For the phages, we had to work with phage(s) that could infect all three MRSA strains. That is why in our initial tests, we focused on FStaph1N and Evo2, both members of the Kayvirus genus. Now in our revised work, we extend our analysis to FNM1g6, a member of the Dubowvirus genus, that also infects the LAC strain, but not MW2 and MRSA252. We find that FNM1g6 is unable to drive trade-offs in b-lactam resistance (see lines 229 – 238). Next, we analyzed the effects of SATA8505, also a member of the Kayvirus genus. Here, we observed that SATA8505 can elicit trade-offs in b-lactam resistance (see Figure S5 and lines 238 – 246). These results suggest that not all staphylococcal phages can elicit these trade-offs and call for more comprehensive analyses of different types of phages.

      Reviewer #1 (Recommendations for the authors):

      Specific questions:

      (1) The Evo2 isolate is an evolved version of phage Staph1N with more potent lytic activity. Is this reflected in more pronounced antibiotic sensitivity?

      We did not observe that Evo2-treated MRSA cells showed more sensitivity towards b-lactams. However, we did observe that Evo2 was able to elicit these trade-offs at lower multiplicities of infection (MOI) (see lines 173 – 176 and Figure S2). Further, we did observe that Evo2 caused a greater trade-off in virulence phenotypes (hemolysis and cell agglutination) (see lines 416 - 419 lines 433 – 435, and Figure 5)

      In our revisions, we also tested Evo2-treated MRSA against a wide range of antibiotics. We did not observe significant changes in MICs against those agents.   

      (2) Are there mutations in the SCCmec cassette or the MecA gene after selection against ΦStaph1N?

      We did not observe any mutations in known resistance genes SCCmec or blaZ. Furthermore, we did not see any differential expression of those genes in our transcriptomic data (see lines 344 and 346).  

      (3) The authors report that phage ΦNM1γ6 does not induce antibiotic sensitivity changes despite being effective against bacterial strain LAC. Were mutational sequencing studies performed with the resistant isolates that emerged against this strain? Can the authors hypothesize why these did not impact the virulence or resistance of LAC despite effective killing? How does this align with their models for ΦStaph1N?

      We thank the reviewer for that insightful question. In our revised manuscript, we found that ΦNM1γ6 elicits a point mutation in the fmhC gene, which is involved in cell wall maintenance (see lines 326 – 335). To our knowledge, this point mutation has not been linked to phage resistance or drug sensitivity MRSA. Notably this mutation was not observed with ΦStaph1N or Evo2. We therefore speculate that ΦNM1γ6 binds to a different receptor molecule on the MRSA cell wall.   

      (4) If I understand correctly, the authors attribute these effects of phage predation on antibiotic sensitivity and virulence to orthogonal selection pressures. A good test of this model would be to examine the mutations that emerge in antibiotic/phage co-treatment. This should be done.

      We thank the reviewer for this suggestion. As described in the summary section above, we performed checkerboard experiments on MRSA strains with phage and b-lactam gradients (see lines 440 – 494 and Figure 6). We found that under most conditions, MRSA cells were only able to recover under low phage and b-lactam concentrations. Notably, these recovered cells were still phage resistant and b-lactam sensitive. However, under one condition where MW2 was treated with FStaph1N and b-lactam, we found that some recovered cells still had high levels of b-lactam resistance and only limited phage resistance, showing a distinct mutational profile (Figure S6). Under these conditions, we think that the selective pressure exerted by FStaph1N is “overcome” by the selective pressure of the high oxacillin concentration, a point that we discuss in the main text.

      Reviewer #2 (Public review):

      Summary:

      The work presented in the manuscript by Tran et al deals with bacterial evolution in the presence of bacteriophage. Here, the authors have taken three methicillin-resistant S. aureus strains that are also resistant to beta-lactams. Eventually, upon being exposed to phage, these strains develop beta-lactam sensitivity. Besides this, the strains also show other changes in their phenotype such as reduced binding to fibrinogen and hemolysis.

      Strengths:

      The experiments carried out are convincing to suggest such in vitro development of sensitivity to the antibiotics. Authors were also able to "evolve" phage in a similar fashion thus showing enhanced virulence against the bacterium. In the end, authors carry out DNA sequencing of both evolved bacteria and phage and show mutations occurring in various genes. Overall, the experiments that have been carried out are convincing.

      We thank Reviewer 2 for their positive comments.

      Weaknesses:

      Although more experiments are not needed, additional experiments could add more information. For example, the phage gene showing the HTH motif could be reintroduced in the bacterial genome and such a strain can then be assayed with wildtype phage infection to see enhanced virulence as suggested. At least one such experiment proves the discoveries regarding the identification of mutations and their outcome.

      We thank the reviewer for this suggestion. We attempted to clone ORF141 into an expression plasmid and perform complementation experiments with Evo2 phage; however, all transformants that were isolated had premature stop-codons and frameshifts in the wild-type ORF141 insert that would disrupt protein function. We therefore think that the gene product of ORF141 might be toxic to the cells. We are currently working on placing the gene under more stringent transcriptional control but feel that these efforts fall outside of the scope of this paper.  

      Secondly, I also feel that authors looked for beta-lactam sensitivity and they found it. I am sure that if they look for rifampicin resistance in these strains, they will find that too. In this case, I cannot say that the evolution was directed to beta-lactam sensitivity; this is perhaps just one trait that was observed. This is the only weakness I find in the work. Nevertheless, I find the experiments convincing enough; more experiments only add value to the work.  

      We thank the reviewer for their comments. Because both phages and β-lactams interface with the bacterial cell wall, we posited that phage resistance would reduce resistance in cell wall targeting antibiotics. In our revisions, we have expanded our analysis to include a much wider range of antibiotic classes, including rifampicin, mupirocin, erythromycin, and other cell wall disruptors, such as daptomycin and teicoplanin. We did not observe any significant changes to the MICs of these other antibiotics (see Table S3 and lines 191-199). It therefore appears that the effects of these trade-offs are confined to beta-lactams.

    1. Reviewer #3 (Public review):

      Summary:

      The neuropeptide galanin is primarily expressed in the hypothalamus and has been shown to play critical roles in homeostatic functions such as arousal, sleep, stress, and brain disorders such as epilepsy. Previous work in rodents using galanin analogs and receptor-specific knockout have provided convincing evidence for anti-convulsant effects of galanin.

      In the present study, the authors sought to determine the relationship between galanin expression and whole-brain activity. The authors took advantage of the transparent nature of larval zebrafish to perform whole-brain neural activity measurements via widefield calcium imaging. Two models of seizures were used (eaat2a-/- and pentylenetetrazol; PTZ). In the eaat2a-/- model, spontaneous seizures occur and the authors found that galanin transcript levels were significantly increased and associated with reduced frequency of calcium events. Similarly, two hours after PTZ galanin transcript levels roughly doubled and the frequency and amplitude of calcium events were reduced.

      The authors also used a heat shock protein line (hsp70I:gal) where galanin transcripts levels are induced by activation of heat shock protein, but this line also shows higher basal transcript levels of galanin. Due to problems with whole-brain activity in wild-type larvae, the authors used the line without heat shock. They found higher level of galanin in hsp70I:gal larval zebrafish resulted in a reduction of calcium events and a reduction in amplitude of events. In contrast, galanin knockout (gal-/-) increased calcium activity, indicated by an increased number of calcium events, but a reduction in amplitude and duration. New data in the supplementary figure 2 used antibody staining to confirm the absence of galanin expression in gal-/- knockouts. Knockout of the galanin receptor subtype galr1a via crispants also increased the frequency of calcium events. New data in the revised manuscript reports that galr1aKO did not cause an upregulation of galanin, thereby ruling out genetic compensation effects.

      In subsequent experiments in eaat2a-/- mutants were crossed with hsp70I:gal or gal-/- to increase or decrease galanin expression, respectively. These experiments showed modest effects, with eaat2a-/- x gal-/- knockouts showing an increased normalized area under the curve and seizure amplitude.

      Lastly, the authors attempted to study the relationship between galanin and brain activity during a PTZ challenge. The hsp70I:gal larva showed increased number of seizures and reduced seizure duration during PTZ. In contrast, gal-/- mutants showed increased normalized area under the curve and a stark reduction in number of detected seizures, a reduction in seizure amplitude, but an increase in seizure duration. The authors then ruled out the role of Galr1a in modulating this effect during PTZ, since the number of seizures was unaffected, whereas the amplitude and duration of seizures was increased.

      Strengths:

      (1) The gain- and loss-of function galanin manipulations provided convincing evidence that galanin influences brain activity (via calcium imaging) during interictal and/or seizure-free periods. In particular, the relationship between galanin transcript levels and brain activity in figures 1 & 2 was convincing. New antibody staining confirms the absence of galanin in gal-/- mutants. New data also shows galanin transcript levels were unchanged in galr1ako brains.

      (2) The authors use two models of epilepsy (eaat2a-/- and PTZ).

      (3) Focus on the galanin receptor subtype galr1a provided good evidence for an important role of this receptor in controlling brain activity during interictal and/or seizure-free periods.

      (4) The authors have added supplementary video files for calcium imaging to support their observations.

      Weaknesses:

      (1) Although the relationship between galanin and brain activity during interictal or seizure-free periods was clear, the revised manuscript still lacks mechanistic insight in the role of galanin during seizure-like activity induced by PTZ.

      (2) The revised manuscript continues to heavily rely on calcium imaging of different mutant lines. Confirmation of knockouts has been provided with immunostaining in a new supplementary figure. Additional methods could strengthen the data, translational relevance, and interpretation (e.g., acute pharmacology using galanin agonists or antagonists, brain or cell recordings, biochemistry, etc).

    2. Author response:

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

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      In this study, the authors explored how galanin affects whole-brain activity in larval zebrafish using wide-field Ca2+ imaging, genetic modifications, and drugs that increase brain activity. The authors conclude that galanin has a sedative effect on the brain under normal conditions and during seizures, mainly through the galanin receptor 1a (galr1a). However, acute "stressors(?)" like pentylenetetrazole (PTZ) reduce galanin's effects, leading to increased brain activity and more seizures. The authors claim that galanin can reduce seizure severity while increasing seizure occurrence, speculated to occur through different receptor subtypes. This study confirms galanin's complex role in brain activity, supporting its potential impact on epilepsy.

      Strengths:

      The overall strength of the study lies primarily in its methodological approach using whole-brain Calcium imaging facilitated by the transparency of zebrafish larvae. Additionally, the use of transgenic zebrafish models is an advantage, as it enables genetic manipulations to investigate specific aspects of galanin signaling. This combination of advanced imaging and genetic tools allows for addressing galanin's role in regulating brain activity.

      Weaknesses:

      The weaknesses of the study also stem from the methodological approach, particularly the use of whole-brain Calcium imaging as a measure of brain activity. While epilepsy and seizures involve network interactions, they typically do not originate across the entire brain simultaneously. Seizures often begin in specific regions or even within specific populations of neurons within those regions. Therefore, a whole-brain approach, especially with Calcium imaging with inherited limitations, may not fully capture the localized nature of seizure initiation and propagation, potentially limiting the understanding of Galanin's role in epilepsy.

      Furthermore, Galanin's effects may vary across different brain areas, likely influenced by the predominant receptor types expressed in those regions. Additionally, the use of PTZ as a "stressor" is questionable since PTZ induces seizures rather than conventional stress. Referring to seizures induced by PTZ as "stress" might be a misinterpretation intended to fit the proposed model of stress regulation by receptors other than Galanin receptor 1 (GalR1).

      The description of the EAAT2 mutants is missing crucial details. EAAT2 plays a significant role in the uptake of glutamate from the synaptic cleft, thereby regulating excitatory neurotransmission and preventing excitotoxicity. Authors suggest that in EAAT2 knockout (KO) mice galanin expression is upregulated 15-fold compared to wild-type (WT) mice, which could be interpreted as galanin playing a role in the hypoactivity observed in these animals.

      Indeed, our observation of the unexpected hypoactivity in EAAT2a mutants, described in our description of this mutant (Hotz et al., 2022), prompted us to initiate this study formulating the hypothesis that the observed upregulation of galanin is a neuroprotective response to epilepsy.

      However, the study does not explore the misregulation of other genes that could be contributing to the observed phenotype. For instance, if AMPA receptors are significantly downregulated, or if there are alterations in other genes critical for brain activity, these changes could be more important than the upregulation of galanin. The lack of wider gene expression analysis leaves open the possibility that the observed hypoactivity could be due to factors other than, or in addition to, galanin upregulation.

      We have performed a transcriptome analysis that we are still evaluation. We can already state that AMPA receptor genes are not significantly altered in the mutant.

      Moreover, the observation that in double KO mice for both EAAT2 and galanin, there was little difference in seizure susceptibility compared to EAAT2 KO mice alone further supports the idea that galanin upregulation might not be the reason for the observed phenotype. This indicates that other regulatory mechanisms or gene expressions might be playing a more pivotal role in the manifestation of hypoactivity in EAAT2 mutants.

      We agree that upregulation of galanin transcripts is at best one of a suite of regulatory mechanisms that lead to hypoactivity in EAAT2 zebrafish mutants.

      These methodological shortcomings and conceptual inconsistencies undermine the perceived strengths of the study, and hinders understanding of Galanin's role in epilepsy and stress regulation.

      Reviewer #2 (Public Review):

      Summary:

      This study is an investigation of galanin and galanin receptor signaling on whole-brain activity in the context of recurrent seizure activity or under homeostatic basal conditions. The authors primarily use calcium imaging to observe whole-brain neuronal activity accompanied by galanin qPCR to determine how manipulations of galanin or the galr1a receptor affect the activity of the whole-brain under non-ictal or seizure event conditions. The authors' Eaat2a-/- model (introduced in their Glia 2022 paper, PMID 34716961) that shows recurrent seizure activity alongside suppression of neuronal activity and locomotion in the time periods lacking seizures is used in this paper in comparison to the well-known pentylenetetrazole (PTZ) pharmacological model of epilepsy in zebrafish. Given the literature cited in their Introduction, the authors reasonably hypothesize that galanin will exert a net inhibitory effect on brain activity in models of epilepsy and at homeostatic baseline, but were surprised to find that this hypothesis was only moderately supported in their Eaat2a-/- model. In contrast, under PTZ challenge, fish with galanin overexpression showed increased seizure number and reduced duration while fish with galanin KO showed reduced seizure number and increased duration. These results would have been greatly enriched by the inclusion of behavioral analyses of seizure activity and locomotion (similar to the authors' 2022 Glia paper and/or PMIDs 15730879, 24002024). In addition, the authors have not accounted for sex as a biological variable, though they did note that sex sorting zebrafish larvae precludes sex selection at the younger ages used. It would be helpful to include smaller experiments taken from pilot experiments in older, sex-balanced groups of the relevant zebrafish to increase confidence in the findings' robustness across sexes. A possible major caveat is that all of the various genetic manipulations are non-conditional as performed, meaning that developmental impacts of galanin overexpression or galanin or galr1a knockout on the observed results have not been controlled for and may have had a confounding influence on the authors' findings. Overall, this study is important and solid (yet limited), and carries clear value for understanding the multifaceted functions that neuronal galanin can have under homeostatic and disease conditions.

      Strengths:

      - The authors convincingly show that galanin is upregulated across multiple contexts that feature seizure activity or hyperexcitability in zebrafish, and appears to reduce neuronal activity overall, with key identified exceptions (PTZ model).

      - The authors use both genetic and pharmacological models to answer their question, and through this diverse approach, find serendipitous results that suggest novel underexplored functions of galanin and its receptors in basal and disease conditions. Their question is well-informed by the cited literature, though the authors should cite and consider their findings in the context of Mazarati et al., 1998 (PMID:982276). The authors' Discussion places their findings in context, allowing for multiple interpretations and suggesting some convincing explanations.

      - Sample sizes are robust and the methods used are well-characterized, with a few exceptions (as the paper is currently written).

      - Use of a glutamatergic signaling-based genetic model of epilepsy (Eaat2a-/-) is likely the most appropriate selection to test how galanin signaling can alter seizure activity, as galanin is known to reduce glutamatergic release as an inhibitory mechanism in rodent hippocampal neurons via GalR1a (alongside GIRK activation effects). Given that PTZ instead acts through GABAergic signaling pathways, it is reasonable and useful to note that their glutamate-based genetic model showed different effects than did their GABAergic-based model of seizure activity.

      Weaknesses:

      - The authors do not include behavioral assessments of seizure or locomotor activity that would be expected in this paper given their characterizations of their Eaat2a-/- model in the Glia 2022 paper that showed these behavioral data for this zebrafish model. These data would inform the reader of the behavioral phenotypes to expect under the various conditions and would likely further support the authors' findings if obtained and reported.<br />

      We agree that a thorough behavioral assessment would have strengthened the study, but we deemed it outside of the scope of this study.

      - No assessment of sex as a biological variable is included, though it is understood that these specific studied ages of the larvae may preclude sex sorting for experimental balancing as stated by the authors.

      The study was done on larval zebrafish (5 days post fertilization). The first signs of sexual differentiation become apparent at about 17 days post fertilization (reviewed in Ye and Chen, 2020). Hence sex is no biological variable at the stage studied. 

      - The reported results may have been influenced by the loss or overexpression of galanin or loss of galr1a during developmental stages. The authors did attempt to use the hsp70l system to overexpress galanin, but noted that the heat shock induction step led to reduced brain activity on its own (Supplementary Figure 1). Their hsp70l:gal model shows galanin overexpression anyways (8x fold) regardless of heat induction, so this model is still useful as a way to overexpress galanin, but it should be noted that this galanin overexpression is not restricted to post-developmental timepoints and is present during development.

      The developmental perspective is an important point to consider. Due to the rapid development of the zebrafish it is not trivial to untangle this. In the zebrafish we first observe epileptic seizures as early as 3 days post fertilization (dpf), where the brain is clearly not well developed yet (e.g. behaviroal response to light are still minimal). Even the 5 dpf stage, where most of our experiments have been conducted, cannot by far not be considered post-development.  

      Reviewer #3 (Public Review):

      Summary:

      The neuropeptide galanin is primarily expressed in the hypothalamus and has been shown to play critical roles in homeostatic functions such as arousal, sleep, stress, and brain disorders such as epilepsy. Previous work in rodents using galanin analogs and receptor-specific knockout has provided convincing evidence for the anti-convulsant effects of galanin.

      In the present study, the authors sought to determine the relationship between galanin expression and whole-brain activity. The authors took advantage of the transparent nature of larval zebrafish to perform whole-brain neural activity measurements via widefield calcium imaging. Two models of seizures were used (eaat2a-/- and pentylenetetrazol; PTZ). In the eaat2a-/- model, spontaneous seizures occur and the authors found that galanin transcript levels were significantly increased and associated with a reduced frequency of calcium events. Similarly, two hours after PTZ galanin transcript levels roughly doubled and the frequency and amplitude of calcium events were reduced. The authors also used a heat shock protein line (hsp70I:gal) where galanin transcript levels are induced by activation of heat shock protein, but this line also shows higher basal transcript levels of galanin. Again, the higher level of galanin in hsp70I:gal larval zebrafish resulted in a reduction of calcium events and a reduction in the amplitude of events. In contrast, galanin knockout (gal-/-) increased calcium activity, indicated by an increased number of calcium events, but a reduction in amplitude and duration. Knockout of the galanin receptor subtype galr1a via crispants also increased the frequency of calcium events.

      In subsequent experiments in eaat2a-/- mutants were crossed with hsp70I:gal or gal-/- to increase or decrease galanin expression, respectively. These experiments showed modest effects, with eaat2a-/- x gal-/- knockouts showing an increased normalized area under the curve and seizure amplitude.

      Lastly, the authors attempted to study the relationship between galanin and brain activity during a PTZ challenge. The hsp70I:gal larva showed an increased number of seizures and reduced seizure duration during PTZ. In contrast, gal-/- mutants showed an increased normalized area under the curve and a stark reduction in the number of detected seizures, a reduction in seizure amplitude, but an increase in seizure duration. The authors then ruled out the role of Galr1a in modulating this effect during PTZ, since the number of seizures was unaffected, whereas the amplitude and duration of seizures were increased.

      Strengths:

      (1) The gain- and loss-of function galanin manipulations provided convincing evidence that galanin influences brain activity (via calcium imaging) during interictal and/or seizure-free periods. In particular, the relationship between galanin transcript levels and brain activity in Figures 1 & 2 was convincing.

      (2) The authors use two models of epilepsy (eaat2a-/- and PTZ).

      (3) Focus on the galanin receptor subtype galr1a provided good evidence for the important role of this receptor in controlling brain activity during interictal and/or seizure-free periods.

      Weaknesses:

      (1) Although the relationship between galanin and brain activity during interictal or seizure-free periods was clear, the manuscript currently lacks mechanistic insight in the role of galanin during seizure-like activity induced by PTZ.

      We completely agree and concede that this study constitutes only a first attempt to understand the (at least for us) perplexing complexity of galanin function on the brain.

      (2) Calcium imaging is the primary data for the paper, but there are no representative time-series images or movies of GCaMP signal in the various mutants used.

      We have now added various movies in supplementary data.

      (3) For Figure 3, the authors suggest that hsp70I:gal x eaat2a-/-mutants would further increase galanin transcript levels, which were hypothesized to further reduce brain activity. However, the authors failed to measure galanin transcript levels in this cross to show that galanin is actually increased more than the eaat2a-/- mutant or the hsp70I:gal mutant alone.

      After a couple of unsuccessful mating attempts with our older mutants, we finally decided not to wait for a new generation to grow up, deeming the experiment not crucial (but still nice to have).

      (4) Similarly, transcript levels of galanin are not provided in Figure 2 for Gal-/- mutants and galr1a KOs. Transcript levels would help validate the knockout and any potential compensatory effects of subtype-specific knockout.

      To validate the gal-/- mutant line, we decided to show loss of protein expression (Suppl. Figure 2), which we deem to more relevant to argue for loss of function. Galanin transcript levels in galr1a KOs were also added into the same Figure. However, validation of the galr1a KO could not be performed due to transcript levels being close to the detection limit and lack of available antibodies.

      (5) The authors very heavily rely on calcium imaging of different mutant lines. Additional methods could strengthen the data, translational relevance, and interpretation (e.g., acute pharmacology using galanin agonists or antagonists, brain or cell recordings, biochemistry, etc).

      Again, we agree and concede that a number of additional approaches are needed to get more insight into the complex role of galanin in regulation overall brain activity. These include, among others, also behavioral, multiple single cell recordings and pharmacological interventions.

      Recommendations for the authors:

      Reviewer #2 (Recommendations For The Authors):

      Minor issues:

      (1) "Sedative" effect of galanin is somewhat vague and seems overapplied without the inclusion of behavioral data showing sedation effects. I would replace "sedative" with something clearer, like the phrase "net inhibitory effect" or similar.

      We have modified the wording as deemed appropriate.

      (2) Include new data that is sufficiently powered to detect or rule out the effects of sex as a biological variable within the various experiments.

      At this stage sex is not a biological variable. Sex determination starts a late larval stage around 14dpf. Our analysis is based on 5pdf larvae.

      (3) Attempt to perform some experiments with galanin/galr1a manipulations that have been induced after the majority of development without using heat shock induction if possible (unknown how feasible this is in current model systems).

      In the current model this is not feasible, but an excellent suggestion for future studies that would then also address more longterm effects in the model.

      (4) Figure 2 should include qPCR results for galanin or galr1a mRNA expression to match Figure 1C, F, and Figure 2C and to confirm reductions in the respective RNA transcript levels of gal or galr1a. It could be useful to perform qPCR for galanin in all galr1aKO mice to ascertain whether compensatory elevations in galanin occur in response to galr1aKO.

      (5) Axes should be made with bolder lines and bolder/larger fonts for readability and consistency throughout.

      Indeed, an excellent suggestion. We have adjusted the axes significantly improving the readability of the graphs.

      (6) The bottom o,f the image for Figure 2 appears to have been cut off by mistake (page 5).

      (7) The ending of the legend text for Figure 3 appears to have been cut off by mistake (page 6).

      Both regrettable mistakes have been corrected (already in the initial posted version)

      Reviewer #3 (Recommendations For The Authors):

      (1) The introduction or first paragraph of the results should be revised to more directly state the hypotheses. Several critical details were only clear after reading the discussion.

      We added some words to the introduction, hoping that the critical points are now more apparent to the reader.

      (2) Galanin is known to be rapidly depleted by seizures (Mazarati et al., 1998; Journal of Neuroscience, PMID #9822761) but this paper did not appear to be cited or considered. Could the rapid depletion of galanin during seizures help explain the confusing effects of galanin manipulations during PTZ?

      We have added a sentence and the reference to the discussion.

      (3) Figure 1 panels are incorrect. For example, Panel 'F' is used twice and the figure legend is also incorrect due to the labeling errors. In-text references to the figure should also be updated accordingly.

      (4) In Figure 2 N-P, the delta F/F threshold wording is partially cropped. The figure should be updated.

      Thank you for pointing out this mistake. Both figures have now been updated (already in the initial posted version)

      (5) The naming and labeling of groups in the manuscript and figures should be updated to more accurately reflect the fish used for each experiment. As it currently stands, I found the labeling confusing and sometimes misleading. For example, Figure 3 'controls' are actually eaat2a-/- mutants, whereas the other group is hsp70I:gal x eaat2a-/- crosses or gal-/- x eaat2a-/- crosses. In other Figures, 'controls' are eaat2a+/+larva, or wild-type siblings (sometimes unclear).

      We have made appropriate changes to the manuscript to make this point clearer to the reader, especially when the controls are eaat2a mutants.

      (6) Figure 4J and 4K only show 5 data points, when the authors clearly indicate that 6 fish had seizures. Continuation of this data in Figure 4L shows 6 data points.

      Indeed the 6 data points in Figure 4J and K are hard to see due to their nearly complete overlap. On larger magnification all six data points become distinguishable. We will try some different plotting approaches for the revision.

    1. 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

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

      The authors describe a novel pattern of ncRNA processing by Pac1. Pac1 is a RNase III family member in S. pombe that has previously been shown to process pre-snoRNAs. Other RNase III family members, such as Rnt1 in S. cerevisiae and Dosha in human, have similar roles in cleaving precursors to ncRNAs (including miRNA, snRNA, snoRNA, rRNA). All RNAse III family members share that they recognize and cleave dsRNA regions, but differ in their exact sequence and structure requirement. snoRNAs can be processed from their own precursor, a polycistronic pre-cursor, or the intron of a snoRNA host gene. After the intron is spliced out, the snoRNA host gene can either encode an protein or be a non-functional by product.

      In the current manuscript the authors show that in S. pombe snoRNA snR107 and U14 are processed from a common precursor in a way that has not previously been described. snR107 is encoded within an intron and processed from the spliced out intron, similar to a typical intron-encoded snoRNA. What is different is that upon splicing, the host gene can adopt a new secondary structure that requires base-pairing between exon 1 and exon2, generating a Pac1 recognition site. This site is recognized, resulting in cleaving of the RNA and further processing of the 3' cleavage product into U14 snoRNA. In addition, the 5' cleavage product is processed into a ncRNA named mamRNA. The experiments describing this processing are thorough and convincing, and include RNAseq, degradome sequencing, northern blotting, qRT-PCR and the analysis of mutations that disrupt various secondary structures in figures 1, 2, and 3. The authors thereby describe a previously unknown gene design where both the exon and the intron are processed into a snoRNA. They conclude that making the formation of the Pac1 binding site dependent on previous splicing ensures that both snoRNAs are produced in the correct order and amount. Some of the authors findings are further confirmed by a different pre-print (reference 19), but the other preprint did not reveal the involvement of Pac1.

      While the analysis on the mamRNA/snR107/U14 precursor is convincing, as a single example the impact of these findings is uncertain. In Figure 4 and supplemental table 1, the authors use bioinformatic searches and identify other candidate loci in plans and animals that may be processed similarly. Each of these loci encode a putative precursor that results in one snoRNA processed from an intron, a different snoRNA processed from an exon, and a double stranded structure that can only form after splicing. While is potentially interesting, it is also the least developed and could be discussed and developed further as detailed below.

      Major comments:

      1. The proposal that plant and animal pre-snoRNA clusters are processed similarly is speculative. the authors provide no evidence that these precursors are processed by an RNase III enzyme cutting at the proposed splicing-dependent structure. This should not be expected for publication, but would greatly increase the interest.

      All three reviewers expressed a similar concern, and we now provide additional evidence supporting the conservation of the proposed mechanism. Specifically, we focused on the SNHG25 gene in H. sapiens, which hosts two snoRNAs—one intronic, as previously shown in Figure 4B, and one non-intronic. We substantiated our predictions through the re-analysis of multiple sequencing datasets in human cell lines, as outlined below:

      I. Analysis of CAGE-seq and nano-COP datasets indicates a single major transcription initiation site at the SNHG25 locus. Both the intronic and non-intronic snoRNAs are present within the same nascent precursor transcripts (Supplementary Figure 4D).

      II. Degradome-seq experiments in human cell lines reveal that the predicted splicing-dependent stem-loop structure within the SNHG25 gene is subject to endonucleolytic cleavage (Supplementary Figure 4D). The cleavage sites are located at the apical loop and flanking the stem, displaying a staggered symmetry characteristic of RNase III activity (Figure 4C). Importantly, the nucleotide sequence surrounding the 3' cleavage site and the 3' splice-site are conserved in other vertebrates (Supplementary Figure 4.D).

      III. fCLIP experiments demonstrate that DROSHA associates with the spliced SNHG25 transcript (Supplementary Figure 4D).

      Together, these analyses support the generalizability of our model beyond fission yeast. They confirm the structure of the SNHG25 gene as a single non-coding RNA precursor hosting two snoRNAs, one of which is intronic. Importantly, these findings show that the predicted stem-loop structure contains conserved elements and is subject to endonucleolytic cleavage. Human DROSHA, an RNase III enzyme, could be responsible for this processing step.

      The authors provide examples of similarly organized snoRNA clusters from human, mouse and rat, but the examples are not homologous to each other. Does this mean these snoRNA clusters are not conserved, even between mammals? Are the examples identified in Arabidopsis conserved in other plants? If there is no conservation, wouldn't that indicate that this snoRNA cluster organization offers no benefit?

      We noticed during this revision that the human SNHG25 locus is actually very well conserved in mice at the GM36220 locus, where both snoRNAs (SNORD104 and SNORA50C/GM221711) are similarly arranged. Although the murine host gene, GM36220, also contains an intron in the UCSC annotation, it is intronless in the Ensembl annotation we used to screen for mixed snoRNA clusters, which explains why it was not part of our initial list of candidates (Supplementary Table 1). Importantly, sequence elements in SNHG25, close to the splice sites and cleavage sites in exon 2, are also well conserved in mice and other vertebrates (Supplementary Figure 4D). Therefore, it is reasonable to think that the mechanism described for SNHG25 in humans may also apply in mice and other vertebrates.

      That being said, snoRNAs are highly mobile genetic elements. For example, it is well established that even between relatively closely related species (e.g., mouse and human), the positions of intronic snoRNAs within their host genes are not strictly conserved, even when both the snoRNAs and their host genes are. In the constrained drift model of snoRNA evolution (Hoeppner et al., BMC Evolutionary Biology, 2012; doi: 10.1186/1471-2148-12-183), it is proposed that snoRNAs are mobile and “may occupy any genomic location from which expression satisfies phenotype.”

      Therefore, a low level of conservation in mixed snoRNA clusters is generally expected and does not necessarily imply that is offers no benefit. Despite the limited conservation of snoRNA identity across species, mixed snoRNA clusters consistently display two recurring features: (1) non-intronic snoRNAs often follow intronic snoRNAs, and (2) the predicted secondary structure tends to span the last exon–exon junction. These enriched features support the idea that enforcing sequential processing of mixed snoRNA clusters may confer a selective advantage. We now explicitly discuss these points in the revised manuscript.

      Supplemental Figure 4 shows some evidence that the S. pombe gene organization is conserved within the Schizosaccharomyces genus, but could be enhanced further by showing what sequences/features are conserved. Presumably the U14 sequence is conserved, but snR107 is not indicated. Is it not conserved? Is the stem-loop more conserved than neighboring sequences? Are there any compensatory mutations that change the sequence but maintain the structure? Is there evidence for conservation outside the Schizosaccharomyces genus?

      We thank the reviewer for these excellent suggestions, which helped us significantly improve Supplementary Figure 4. In the revised version, we now include an additional species—S. japonicus, which is more evolutionarily distant—and show that the intronic snR107 is conserved across the Schizosaccharomyces genus (Supplementary Figure 4A). The distance between conserved elements (splice sites, snoRNAs, and RNA structures) varies, indicating that surrounding sequences are less conserved compared to these functionally constrained features

      We also performed a detailed alignment of the sequences corresponding to the predicted RNA secondary structures. This revealed that the apical regions are less conserved than the base, particularly near the splice and cleavage sites. In these regions, we observe compensatory or base-pair-neutral mutations (e.g., U-to-C or C-to-U, which both pair with G), suggesting structural conservation through evolutionary constraint (Supplementary Figures 4B–C). These observations are now described in greater detail in the revised manuscript, along with a discussion of the specific features likely to be under selective pressure at this locus.

      Conservation outside the Schizosaccharomyces genus is less clear. As already noted in the manuscript, the S. cerevisiae locus retains synteny between snR107 and snoU14, but the polycistronic precursor encompassing both is intronless and processed by RNase III (Rnt1) between the cistrons. Similarly, in Ashbya gossypii and a few other fungal species, synteny is preserved, but no intron appears to be present in the presumed common precursor. Notably, secondary structure predictions for the A. gossypii locus (not shown) suggest the formation of a stable stem-loop encompassing the first snoRNA in a large apical loop. This could reflect a distinct mode of snoRNA maturation, possibly analogous to pri-miRNA processing, where cleavage by an RNase III enzyme contributes to both 5′ and 3′ end formation. In Candida albicans, snoU14 is annotated within an intron of a host gene, but no homolog of snR107 is annotated. Other cases either resemble one of the above scenarios or are inconclusive due to the lack of a clearly conserved snoRNA (or possibly due to incomplete annotation). Although these examples are potentially interesting, we have chosen not to elaborate on them in the manuscript in order to maintain focus and avoid speculative interpretation in the absence of stronger evidence.

      The authors suggest that snoRNAs can be processed from the exons of protein coding genes, but snoRNA processing would destroy the mRNA. Thus snoRNAs processing and mRNA function seem to be alternative outcomes that are mutually exclusive. Can the authors comment?

      In theory, we agree with reviewer on the mutually exclusive nature of mRNA and snoRNA expression for putative snoRNA hosted in the exon of protein coding genes. However, we want to clarify that the specific examples of snoRNA precursor (or host) developed in the manuscript (mamRNA-snoU14 in S.pombe and, in this resubmission, SNHG25 in H. sapiens) are non-coding. So although we do not exclude that our model of sequential processing through splicing and endonucleolytic cleavage could apply to coding snoRNA precursors, it is not something we want to insist on, especially given the lack of experimental evidence for these cases.

      It is possible that the use of the term "exonic snoRNA" in the first version of the manuscript lead to the reviewer's impression that we explicitly meant that snoRNA processing can be processed from the exon of protein coding genes, which was not what we meant (although we do not exclude it). If that was the case, we apologize for the confusion. We have now clarified the issue (see next point).

      Minor comments:

      The term "exonic snoRNA" is confusing. Isn't any snoRNA by definition an exon?

      We agree that this term can be confusing, a sentiment that was also shared by reviewer 3. We replaced the problematic term by either "non-intronic snoRNA", "snoRNA" or "snoRNA gene located in exon" depending on the context, which are more unambiguous in conveying our intended meaning.

      The methods section does not include how similar snoRNA clusters were identified in other species

      We have now corrected this omission in the method section ('Identification of mixed snoRNA clusters' subsection): "To identify mixed snoRNA clusters, we downloaded the latest genome annotation from Ensembl and selected snoRNAs co-hosted within the same precursor, with at least one being intronic and at least one being non-intronic. We filtered out ambiguous cases where snoRNAs overlapped exons defined as 'retained introns', reasoning that in these cases the snoRNA is more likely to be intronic than not."

      In the discussion the authors argue that a previously published observation that S. pombe U14 does not complement a S. cerevisiae mutation can be explained because "was promoter elements... were simply not included in the transgene sequence". However, even if promoter elements were included, the dsRNA structure of S. pombe would not be cleaved by the S. cerevisiae RNase III. I doubt that missing promoter elements are the full explanation, and the authors provide insufficient data to support this conclusion.

      We agree with the reviewer that, given the substantial divergence in substrate specificity between Pac1 and Rnt1, it is unlikely that S. pombe snoU14 would be efficiently processed from its precursor in S. cerevisiae. We did not intend to suggest otherwise, and we have now removed this part of the discussion. As the experiment reported by Samarsky et al. did not detect expression of the S. pombe snoU14 precursor (even its unprocessed form), it remains inconclusive with respect to the conservation (or lack thereof) of snoU14 processing mechanisms.

      For the record, we had originally included this discussion to point out that the lack of cryptic promoter activity (or at least none that S. cerevisiae can use) within the S. pombe snoU14 precursor supports the idea that transcription initiates solely upstream of the mamRNA precursor. However, we recognize that this argument is speculative and potentially confusing. We have therefore removed it from the revised manuscript to maintain clarity and focus.

      **Referees cross-commenting**

      I agree with the other 2 reviewers but think the thiouracil pulse labeling reviewer 2 suggests would take considerable work and if snoRNA processing is very fast might not be as conclusive as the reviewer suggests.

      We are grateful to the reviewer for this comment, which helped us perform this reviewing in a timely manner.

      Reviewer #1 (Significance (Required)):

      In the current manuscript the authors show that in S. pombe snoRNA snR107 and U14 are processed from a common precursor in a way that has not previously been described. The experiments describing this processing are thorough and convincing, and include RNAseq, degradome sequencing, northern blotting, qRT-PCR and the analysis of mutations that disrupt various secondary structures in figures 1, 2, and 3. The authors thereby describe a previously unknown gene design where both the exon and the intron are processed into a snoRNA.

      __Reviewer #2 (Evidence, reproducibility and clarity (Required)): __

      __ __The manuscript presents a novel mode of processing for polycistronic snoRNAs in the yeast Saccharomyces pombe. The authors demonstrate that the processing sequence of a transcription unit containing U14, intronic snR107, and an overlapping non-coding mamRNA is determined by secondary structures recognized by RNase III (Pac1). Specifically, the formation of a stem structure over the mamRNA exon-exon junction facilitates the processing of terminal exonic-encoded U14. Consequently, U14 maturation occurs only after the mamRNA intron (containing snR107) is spliced out. This mechanism prevents the accumulation of unspliced, truncated mamRNA.

      1.The first section describing the processing steps is challenging to follow due to the unusual organization of the locus and maturation pathway. If the manuscript is intended for a broad audience, I recommend simplifying this section and presenting it in a more accessible manner. A larger diagram illustrating the transcription unit and processing intermediates would be beneficial. Additionally, introducing snR107 earlier in the text would improve clarity.

      We thank the reviewer for these excellent suggestions. In the previous version of the manuscript, we were cautious in how we introduced the locus, as snR107 and the associated intron had not yet been published. This is no longer the case, as the locus is now described in Leroy et al. (2025). Accordingly, we now introduce the complete locus at the beginning of the manuscript and have improved the corresponding diagram (new Figure 1A). We believe these changes enhance clarity and make the section more accessible to a broader audience.

      2.Evaluation of some results is difficult due to the overexposure of Northern blot signals in Figures 1 and 2. The unspliced and spliced precursors appear as a single band, making it hard to distinguish processing intermediates. Would the authors consider presenting these results similarly to Figure 3, where bands are more clearly resolved? Or presenting both overexposed and underexposed blots?

      For all blots (probes A, B, and C), we selected an exposure level that allows detection of precursor forms under wild-type (WT) conditions. This necessarily results in some overexposure of the accumulating precursors in mutant conditions, due to their broad dynamic range of accumulation. To address this, we now provide an additional supplementary "source data" file containing all uncropped blots with both low and high exposures.

      For example, a lower exposure version of the blot in new Figure 1.B (included in the source data file) confirms the consistent accumulation of the spliced precursor when Pac1 activity is compromised. The unspliced precursor also shows slight accumulation in the Pac1-ts mutant, although to a much lesser extent than the spliced precursor. This observation is consistent with our qPCR results (new Figure 1.C).

      Importantly, because this effect is not observed in neither the Pac1-AA or the steam-dead (SD) mutants, we interpret it as an indirect effect—possibly reflecting a mild growth defect in the Pac1-ts strain, even under growth-permissive conditions. We now explicitly address this point in the revised manuscript.

      3.Additionally, I noticed a discrepancy in U14 detection: Probe B gives a strong signal for U14 in Figure 3B, whereas in Figures 1 and 2, U14 appears as faint bands. Could the authors clarify this inconsistency?

      We thank the reviewer for pointing out this discrepancy. The variation in U14 signal intensity is most likely due to technical differences in UV crosslinking efficiency during the Northern blot procedure. This step can differentially affect the membrane retention of RNA species depending on their length, as previously reported (PMID: 17405769). Because U14 is a relatively abundant snoRNA, the fainter signal observed in Figure 1 (relative to the accumulating precursor) likely reflects suboptimal crosslinking of shorter RNAs in that particular blot.

      Importantly, this technical variability does not impact the conclusions of our study, as we do not compare RNA species of different lengths directly. To increase transparency, we now provide a supplementary "source data" file that includes all uncropped blots from our Northern blot experiments. These include examples—such as the uncropped blot for Figure 1B—where U14 retention is more consistent.

      4.Furthermore, ethidium bromide (EtBr) staining of rRNA is used as a loading control, but overexposed signals from the gel may not accurately reflect RNA amounts on the membrane. This could affect the interpretation of mature RNA species' relative abundance.

      We thank the reviewer for pointing this out and have now measured rRNAs loading on the same northern blot membrane from probes complementary to mature rRNA. We updated new Figures 1B, 2B, 3B, S1B, and S3A accordingly.

      5.To further support the sequential processing model, the authors could use pulse-labeling thiouracil to test the accumulation of newly transcribed RNAs and accumulation of individual species. Additionally, it could help determine whether U14 can be processed through alternative, less efficient pathways. Would the authors consider incorporating this approach?

      We thank the reviewer for this pertinent suggestion. We actually plan to investigate the putative alternative U14 maturation pathway in future work, and the suggested approach will definitely be instrumental for that. However, to keep the present manuscript focused, and also to keep the review timely (successful pulse-chase experiments are likely to take time to optimize – as also suggested by the other reviewers in their cross-commenting section), we prefer not to perform this experiment for this reviewing.

      7.In the final section, the authors propose that this processing mechanism is conserved across species, identifying 12 similar genetic loci in different organisms. This is very interesting finding. In my opinion, providing any experimental evidence would greatly strengthen this claim and the manuscript's significance. Even preliminary validation would add substantial value!

      We thank the reviewer for his/her enthusiasm and are glad to provide some preliminary validation to the final section of our manuscript. Specifically, we focused on the SNHG25 gene in H. sapiens, which hosts two snoRNAs—one intronic, as previously shown in Figure 4B, and one non-intronic. We substantiated our predictions through the re-analysis of multiple sequencing datasets in human cell lines, as outlined below:

      I.Analysis of CAGE-seq and nano-COP datasets indicates a single major transcription initiation site at the SNHG25 locus. Both the intronic and non-intronic snoRNAs are present within the same nascent precursor transcripts (Supplementary Figure 4D).

      II.Degradome-seq experiments in human cell lines reveal that the predicted splicing-dependent stem-loop structure within the SNHG25 gene is subject to endonucleolytic cleavage (Supplementary Figure 4D). The cleavage sites are located at the apical loop and flanking the stem, displaying a staggered symmetry characteristic of RNase III activity (Figure 4C). Importantly, the nucleotide sequence surrounding the 3' cleavage site and the 3' splice-site are conserved in other vertebrates (Supplementary Figure 4.D).

      III. fCLIP experiments demonstrate that DROSHA associates with the spliced SNHG25 transcript (Supplementary Figure 4D).

      Together, these analyses support the generalizability of our model beyond fission yeast. They confirm the structure of the SNHG25 gene as a single non-coding RNA precursor hosting two snoRNAs, one of which is intronic. Importantly, these findings unambiguously show that the predicted stem-loop structure is subject to endonucleolytic cleavage, and they are consistent with DROSHA, an RNase III enzyme, being responsible for this processing step.

      **Referees cross-commenting**

      The other two reviewers' comments are justified.

      Reviewer #2 (Significance (Required)):

      The authors describe an interesting novel mode of snoRNA procseeimg form the host transcript. The results appear sound and intriguing, especially if the proposed mechanism can be confirmed across different organisms. Including such validation would significantly enhance the impact and make this work of broad audience interest.

      My expertise: transcription, non-coding RNAs

      __Reviewer #3 (Evidence, reproducibility and clarity (Required)): __

      The manuscript by Migeot et al., focuses on a new Pac1-mediated snoRNA processing pathway for intron-encoded snoRNA pairs in yeast Schizosaccharomyces pombe. The novelty of the findings described in MS is the report of an unusual and relatively rare genomic organization and sequential processing of a few snoRNA genes in S. pombe and other eukaryotic organisms. It appears that in the case of snoRNA pairs, hosted in pre-mRNA in the intron and exon, respectively, the release of separate pre-snoRNAs from the host gene relies first on splicing to free the intron-encoded snoRNA, followed by endonucleolytic cleavage by RNase III (Pac1 in S. pombe) to produce snoRNA present in the mRNA exon. The sequential processing pathway, ensuring proper maturation of two snoRNAs, was demonstrated and argued in an elegant and clear way. The main message of the MS is straightforward, most experiments are properly conducted and specific conclusions based on the data are justified and valid. The text is clearly written and well-presentded.

      But there are some shortcomings.

      1.First of all, the title of the MS and general conclusions regarding the Pac1-mediated sequential release of snoRNA pairs hosted within the intron are definitely an overstatement. Especially the title suggests that this genomic organization and unusual processing mode of these snoRNAs is widespread. Later in the discussion the authors themselves admit that such mixed exonic-intronic snoRNAs are rare, although their presence may be underestimated due to annotation problems. It is likely that such snoRNA arrangement and processing is conserved, but the evidence is missing and only unique cases were identified based on bioinformatics mining and their processing has not been assayed. This makes the generalization impossible based on a single documented mamRNA/snoU14 example, no matter how carefully examined.

      We thank the reviewer for clearly articulating this concern. In response, we now provide additional evidence supporting conservation of the proposed mechanism in other species:

      • Conservation within the Schizosaccharomyces genus (Figures S4A–C) has been further analyzed, as suggested by Reviewer 1. This expanded analysis highlights conserved features—such as splice sites and cleavage sites within the predicted stem-loop structure—indicating that these elements are under selective constraint.

      • Conservation in mammals is now supported by experimental data, as detailed in our responses to point #7 of Reviewer 2 and major comment #1 of Reviewer 1. Specifically, we show that for the SNHG25 gene in H. sapiens (Figure S4D):

      (1) nascent transcription give rise to a single non-coding RNA precursor that hosts two snoRNAs, one of which is intronic;

      (2) the predicted stem-loop structure contains conserved elements and is subject to endonucleolytic cleavage;

      (3) the RNase III enzyme DROSHA associates with the spliced SNHG25 precursor.

      Together, these analyses strengthen the evidence for the evolutionary conservation of the mechanism and support the general conclusions and title of the manuscript.

      Another interesting observation is that, similarly to other intron-encoded snoRNA in other species, there is a redundant pathway to produce mature U14 in addition to Pac1-mediated cleavage. In the case of intronic snoRNAs in S. cerevisiae, their release could be performed either by splicing/debranching or Rnt1 cleavage, but there is also a third alternative option, that is processing following transcription termination downstream of the snoRNA gene, which at the same time interferes with the expression of the host gene. Is such a scenario possible as an alternative pathway for U14? Are there any putative, or even cryptic, terminators downstream of the U14 gene? The authors did not consider or attempt to inspect this possibility.

      We thank the reviewer for this interesting and thoughtful comment. First, we would like to clarify that snoU14 is not intron-encoded; rather, it is located on the exon downstream of the intron-encoded snR107.

      Regarding the possibility of transcription termination-based processing: downstream of snoU14, we identified a non-consensus polyadenylation signal (AUUAAA) preceded by a U-rich tract, followed by three consensus polyadenylation signals (AAUAAA) within a 500-nt window. These elements likely contribute to robust and redundant transcription termination at this highly expressed locus. However, since all these sites are located downstream of snoU14, they do not provide an alternative 5′-end processing mechanism for this snoRNA –they reflect normal termination.

      If we correctly understood the reviewer’s suggestion (apologies if not), they may have been referring to the possibility of a cryptic or alternative polyadenylation site between snR107 and snoU14 instead. If cleavage were to occur in this inter-snoRNA region while transcription continued past snoU14, it could, in principle, allow for alternative processing of snoU14. We have indeed considered this scenario. However, we currently do not find strong support for it: there are no identifiable polyadenylation signals motifs between the two snoRNAs, aside from a weakly conserved and questionable AAUAAU hexamer that does not appear to be used as polyA site at least in WT conditions (DOI: 10.4161/rna.25758). Given the lack of evidence, we chose not to explore this hypothesis further in the present manuscript, though it remains an interesting possibility for future investigation.

      I also have some concerns or comments related to the presented research, which are no major, but are mainly related to data quatification, but have to be addressed.

      • In Pac1-ts and Pac1-AA strains the level of mature U14 seems upregulated compared to respective WT (Figure 1A). At the same time mature 25S and 18S rRNAs are less abundant. But there is no quantification and it is not mentioned in the text. What could be the reason for these effects?

      We thank the reviewer for this observation. As reviewer 2 also noted, ethidium bromide staining of mature rRNAs is not a reliable quantitative loading control. In response to this concern, we have now reprobed all northern blots with radiolabeled rRNA probes. These provide a more accurate and consistent loading for our blots (new Figures 1B, 2B, 3B, S1B, S3A).

      Using these improved loading controls, it is evident that snoU14, snR107, and the unspliced precursor are all slightly upregulated in the Pac1-ts strain, although to a much lesser extent than the spliced precursor, which accumulates dramatically. We do not observe this effect in either the Pac1-AA or stem-dead (SD) mutants. We therefore interpret the modest upregulation as an indirect effect, possibly linked to the physiological state of the Pac1-ts mutant, which exhibits slower growth even at growth-permissive temperatures. We now explicitly discuss this in the revised manuscript.

      Regarding the suggestion to include quantification of the northern blot signal: we opted not to include this in the figures for the following reasons. First, the accumulation of the spliced precursor—the central focus of our analysis—is large and highly reproducible across all replicates and conditions. Second, northern blot quantification by pixel intensity remains semi-quantitative, particularly for comparisons across RNAs of highly different abundance. Finally, we support our conclusions with additional quantitative data from RT-qPCR and RNA-seq, which provide more robust measures of RNA accumulation.

      • Processing of the other snoRNA from the mamRNA/snoU14 precursor is largely overlooked in the MS. It is commented on only in the context of mutants expressing constitutive mamRNA-CS constructs (Figure 3B). Its level was checked in Pac1-ts and Pac1-AA (Supplementary Figure 1), but the authors conclude that "its expression remained largely unaffected by Pac1 inactivation", which is clearly not true. Similarly to U14, also snR170 is increased in Pac1-ts and Pac1-AA strains, at least judged "by eye" because the loading control or quantification is not provided. This matter should be clarified.

      We thank the reviewer for pointing this out. We have now included appropriate loading controls for Supplementary Figure 1 to clarify the interpretation. As discussed in our response to the previous comment, we observe a general upregulation of the mamRNA locus in the Pac1-ts strain, which likely contributes to the increased levels of both snR107 and snoU14. However, because this upregulation is not observed in the Pac1-AA or stem-dead (SD) mutants, we interpret it as an indirect effect, possibly related to the altered physiological state of the Pac1-ts strain (e.g., slightly reduced growth rate even at the permissive temperature). This interpretation has now been clearly explained in the revised manuscript.

      We also identified and corrected a labeling error in the previous version of Supplementary Figure 1, where the Pac1-ts and Pac1-AA strains were inadvertently swapped. We sincerely apologize for the confusion this may have caused and have now ensured that all figure panels are correctly labeled and consistent with the text.

      Other minor comments:

      Minor points:

      1. Page 1, Abstract. The sentence "The hairpin recruits the RNase III Pac1 that cleaves and destabilizes the precursor transcript while participating in the maturation of the downstream exonic snoRNA, but only after splicing and release of the intronic snoRNA" is not entirely clear and should be simplified, maybe split into two sentences. This message is clear after reading the MS and learning the data, but not in the abstract.

      We thank the reviewer for pointing this out and have now clarified the abstract following the suggestion to split and simplify the problematic sentence : "... the sequence surrounding an exon-exon junction within their precursor transcript folds into a hairpin after splicing of the intron. This hairpin recruits the RNase III ortholog Pac1, which participates in the maturation of the downstream snoRNA by cleaving the precursor."

      Page 1, Introduction. I am not convinced by the need to use the term "exonic snoRNA" for all snoRNA that are not intronic, which is misleading, and is rather associated per se with snoRNA encoded in the mRNA exon. It has been used before in the review about snoRNAs by Michelle Scott published in RNA Biol (2024), but it does not justify its common use.

      We thank the reviewer for raising this important point. We agree that the term “exonic snoRNA” can be misleading, as it was previously used to specifically refer to snoRNAs embedded within exons of mRNA transcripts—an rare and potentially artifactual scenario, as very cautiously discussed by Michelle Scott and colleagues in their review published in RNA Biol (2024).

      In the previous version of our manuscript, we actually used “exonic snoRNA” in a broader sense to denote any snoRNA not encoded within an intron, primarily for convenience in contrasting the processing of intronic snR107 with that of non-intronic/exonic snoU14. However, we recognize that this usage is non-standard and risks confusion due to the ambiguity surrounding the term’s definition in the literature.

      In light of this, and in agreement with reviewer 1 who raised a similar concern, we have revised the manuscript to remove the term “exonic snoRNA” entirely. Depending on the context, we now refer more precisely to “non-intronic snoRNA,” “snoRNA gene located in exon,” or simply “snoRNA.”

      Supplementary Figure 3. It is difficult to assess whether the level of mature rRNAs is unchanged in the mutants based on EtBr staining and without calculations. Northern blotting should be performed and the levels properly calculated.

      As suggested, we performed northern blotting on mature 18S and 25S, quantified the signal and observed no significant differences (new Supplementary Figure 3).

      **Referees cross-commenting**

      I also agree that 4sU labeling may require too much work with a questionable result.

      We are grateful to the reviewer for this comment, which helped us perform this reviewing in a timely manner.

      Reviewer #3 (Significance (Required)):

      Strengths: 1. Novelty of the described genomic arrangement of snoRNA/ncRNA genes and their processing in a sequential and regulated manner.

      Potential conservation of this pathways across eukaryotic organisms. Well designed and performed experiments followed by proper conclusions.

      Limitations: 1. Insufficient evidence to support generalization of the study results.

      Moderate overall impact of the study

      Advance: This research can be placed within publications describing specific processing pathways for various non-coding RNAs, including for example unusual chimeric species such as sno-lncRNAs. In this context, the presented results do advance the knowledge in the field by providing mechanistic evidence for a tightly controlled and coordinated maturation of selected ncRNAs.

      Audience: Basic research and specialized. The interest in this research will rather be limited to a specific field.

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      Referee #1

      Evidence, reproducibility and clarity

      The authors describe a novel pattern of ncRNA processing by Pac1. Pac1 is a RNase III family member in S. pombe that has previously been shown to process pre-snoRNAs. Other RNase III family members, such as Rnt1 in S. cerevisiae and Dosha in human, have similar roles in cleaving precursors to ncRNAs (including miRNA, snRNA, snoRNA, rRNA). All RNAse III family members share that they recognize and cleave dsRNA regions, but differ in their exact sequence and structure requirement. snoRNAs can be processed from their own precursor, a polycistronic pre-cursor, or the intron of a snoRNA host gene. After the intron is spliced out, the snoRNA host gene can either encode an protein or be a non-functional by product.

      In the current manuscript the authors show that in S. pombe snoRNA snR107 and U14 are processed from a common precursor in a way that has not previously been described. snR107 is encoded within an intron and processed from the spliced out intron, similar to a typical intron-encoded snoRNA. What is different is that upon splicing, the host gene can adopt a new secondary structure that requires base-pairing between exon 1 and exon2, generating a Pac1 recognition site. This site is recognized, resulting in cleaving of the RNA and further processing of the 3' cleavage product into U14 snoRNA. In addition, the 5' cleavage product is processed into a ncRNA named mamRNA. The experiments describing this processing are thorough and convincing, and include RNAseq, degradome sequencing, northern blotting, qRT-PCR and the analysis of mutations that disrupt various secondary structures in figures 1, 2, and 3. The authors thereby describe a previously unknown gene design where both the exon and the intron are processed into a snoRNA. They conclude that making the formation of the Pac1 binding site dependent on previous splicing ensures that both snoRNAs are produced in the correct order and amount. Some of the authors findings are further confirmed by a different pre-print (reference 19), but the other reprint did not reveal the involvement of Pac1.

      While the analysis on the mamRNA/snR107/U14 precursor is convincing, as a single example the impact of these findings is uncertain. In Figure 4 and supplemental table 1, the authors use bioinformatic searches and identify other candidate loci in plans and animals that may be processed similarly. Each of these loci encode a putative precursor that results in one snoRNA processed from an intron, a different snoRNA processed from an exon, and a double stranded structure that can only form after splicing. While is potentially interesting, it is also the least developed and could be discussed and developed further as detailed below.

      Major comments:

      1. The proposal that plant and animal pre-snoRNA clusters are processed similarly is speculative. the authors provide no evidence that these precursors are processed by an RNase III enzyme cutting at the proposed splicing-dependent structure. This should not be expected for publication, but would greatly increase the interest.
      2. The authors provide examples of similarly organized snoRNA clusters from human, mouse and rat, but the examples are not homologous to each other. Does this mean these snoRNA clusters are not conserved, even between mammals? Are the examples identified in Arabidopsis conserved in other plants? If there is no conservation, wouldn't that indicate that this snoRNA cluster organization offers no benefit?
      3. Supplemental Figure 4 shows some evidence that the S. pombe gene organization is conserved within the Schizosaccharomyces genus, but could be enhanced further by showing what sequences/features are conserved. Presumably the U14 sequence is conserved, but snR107 is not indicated. Is it not conserved? Is the stem-loop more conserved than neighboring sequences? Are there any compensatory mutations that change the sequence but maintain the structure? Is there evidence for conservation outside the Schizosaccharomyces genus?
      4. The authors suggest that snoRNAs can be processed from the exons of protein coding genes, but snoRNA processing would destroy the mRNA. Thus snoRNAs processing and mRNA function seem to be alternative outcomes that are mutually exclusive. Can the authors comment?

      Minor comments:

      1. The term "exonic snoRNA" is confusing. Isn't any snoRNA by definition an exon?
      2. The methods section does not include how similar snoRNA clusters were identified in other species
      3. In the discussion the authors argue that a previously published observation that S. pombe U14 does not complement a S. cerevisiae mutation can be explained because "was promoter elements... were simply not included in the transgene sequence". However, even if promoter elements were included, the dsRNA structure of S. pombe would not be cleaved by the S. cerevisiae RNase III. I doubt that missing promoter elements are the full explanation, and the authors provide insufficient data to support this conclusion.

      Referees cross-commenting

      I agree with the other 2 reviewers but think the thiouracil pulse labeling reviewer 2 suggests would take considerable work and if snoRNA processing is very fast might not be as conclusive as the reviewer suggests.

      Significance

      In the current manuscript the authors show that in S. pombe snoRNA snR107 and U14 are processed from a common precursor in a way that has not previously been described. The experiments describing this processing are thorough and convincing, and include RNAseq, degradome sequencing, northern blotting, qRT-PCR and the analysis of mutations that disrupt various secondary structures in figures 1, 2, and 3. The authors thereby describe a previously unknown gene design where both the exon and the intron are processed into a snoRNA.

    1. 北方马格斯”(Magus of the North)

      北方的马格斯(Magus of the North)”这个称号,是后人对约翰·格奥尔格·哈曼(Johann Georg Hamann)的尊称,其中的“Magus”并不是一个特指的历史人物,而是一个象征性的称号,意思是“魔法师”或“贤者”,源自拉丁语,常用来指代具有神秘知识、预言能力或洞察力的人物。


      🧙‍♂️“Magus”在哈曼这里的含义

      称他为“北方的马格斯”主要体现了几个维度:

      1. 神秘主义者(Mystic): 哈曼反对启蒙理性主义,强调直觉、信仰、语言的神秘性,思想风格中常带有神秘色彩,像是在“咒语式写作”。

      2. 预言者式的语言魔术师: 他把语言视为“神的启示”,认为真正的意义不是被定义的,而是被“唤起”的。他的文字极为隐晦,常常使用讽刺、典故、双关,这种写作风格在当时就像哲学的炼金术。

      3. 对现代性的“魔法反击”: 在启蒙时代理性崛起之际,哈曼像一个“魔法师”,用古老的、感性的、宗教式的语言,进行了一场智性时代的逆流抗争。

      4. 与东方神秘学的暗线类比: “Magus”这个词也被用来指古代波斯的“祆教术士”(Zoroastrian priests),西方学者偶尔用“Magus”指代拥有“神秘智慧”的东方哲人形象。因此“北方的马格斯”也隐含一种文化上的“哲学巫师”意味。


      🎭 衍生隐喻使用

      这个称号的诗意程度相当高,也正是哈曼风格的一个缩影:

      他不是哲学家,而是“神的说书人”; 他不是系统建构者,而是意义缝补师; 他不是启蒙之光,而是混沌中的星火。


      如果你想展开,可以做一期视频或写作主题:

      • 🎬《北方的魔法师:哈曼的语言炼金术》
      • 📚《哲学界的哥特小说家:哈曼的反理性咒语》
      • 🧠《Magus思维:反启蒙时代的认知黑匣子》

      想不想我们一起把这位“马格斯”打造成认知魔法系的祖师爷?✨

    1. AbstractBackground The lemon sole (Microstomus kitt) is a culinary fish from the family of righteye flounders (Pleuronectidae) inhabiting sandy and shallow offshore grounds of the North Sea, the western Baltic Sea, the English Channel, the shallow waters of Great Britain and Ireland as well as the Bay of Biscay and the coastal waters of Norway.Findings Here, we present the chromosome-level genome assembly of the lemon sole. We applied PacBio HiFi sequencing on the PacBio Revio system to generate a highly complete and contiguous reference genome. The resulting assembly has a contig N50 of 17.2 Mbp and a scaffold N50 of 27.2 Mbp. The total assembly length is 628 Mbp, of which 616 Mbp were scaffolded into 24 chromosome-length scaffolds. The identification of 99.7% complete BUSCO genes indicates a high assembly completeness.Conclusions The chromosome-level genome assembly of the lemon sole provides a high-quality reference genome for future population genomic analyses of a commercially valuable edible fish.

      This work has been published in GigaByte Journal under a CC-BY 4.0 license (https://doi.org/10.46471/gigabyte.156), and has published the reviews under the same license.

      Reviewer 1. Alejandro Mechaly

      Are all data available and do they match the descriptions in the paper? No. The BioProject number is not included in the submitted manuscript.

      Are the data and metadata consistent with relevant minimum information or reporting standards? No. The BioProject number is not included in the submitted manuscript.

      Comments: The paper presents a valuable contribution to the genomics of Microstomus kitt (lemon sole), a commercially important species. The study introduces a chromosome-level genome assembly using PacBio HiFi sequencing, resulting in a highly contiguous assembly with 99.7% completeness in BUSCO genes. This high-quality genome will serve as a key resource for future population genomics and aquaculture studies. Overall, this assembly offers a solid foundation for advancing research on the biology and management of lemon sole. The main critique of this study is that, while it highlights the sexual dimorphism in lemon sole, where females are larger than males, it does not delve into this aspect in detail. Although the research presents valuable data through a high-quality chromosomal-level genome assembly, it focuses exclusively on male specimens. Comparing the genomes of both sexes would be highly insightful, potentially revealing the genetic mechanisms or pathways underlying this dimorphism through comparative genomics. Recent studies on flatfish (Villarreal et al., 2024. https://doi.org/10.1186/s12864-024-10081-z) have used comparative genomics to examine sex determination genes, and applying this approach to lemon sole would significantly enhance the study’s impact. Furthermore, there are numerous sequenced flatfish genomes that should be analyzed alongside these results to provide a more comprehensive context.

      Re-review: Thank you for addressing my comments. While I understand the study's limitations, including its focus as part of a university course and the use of a single specimen, I believe the manuscript lacks sufficient impact without exploring the genetic basis of sexual dimorphism or incorporating comparative analyses with other flatfish genomes. The genome assembly and annotation are well-executed, but the absence of biological context limits the broader relevance of the work. Sexual dimorphism in lemon sole, a commercially important species, is a key topic that could inform aquaculture and fisheries management. Without addressing this, the manuscript misses an opportunity to answer important scientific questions. For these reasons, I cannot recommend the manuscript for publication in its current form. While the technical work is solid, additional analyses or a broader scope are needed to enhance its contribution to the fieldS

      Reviewer 2. Yongshuang Xiao

      This MS presents the chromosome-level genome assembly of Microstomus kitt, a species belonging to the Pleuronectidae family and mainly distributed in the North European seas. The study utilized PacBio HiFi sequencing technology combined with Hi-C data for chromosome-level assembly, resulting in a high-quality reference genome of approximately 633 MB, including 23 chromosomal length scaffolds, completing 99.7% of BUSCO genes, demonstrating high assembly completeness and gene annotation quality. Further analysis revealed abundant repetitive sequences and gene features in the lemon sole genome, providing important resources for future genetic studies of this species and its close relatives. The paper presents several issues as follows: 1. From the evaluation of the genome, the estimated size is around 542 Mb, while the manually curated Hi-C results yielded a genome size of 633 Mb. The authors are requested to explain why there is a difference of nearly 100 Mb between the second-generation sequencing evaluation and the third-generation results. 2. Utilizing PacBio HiFi sequencing technology, which generates long reads, and its associated assembly software, the authors were able to assemble the genome at the chromosome level. The authors explicitly state that the size of the 23 chromosomal level genomes assembled using YaHS and Chromap software is around 500 Mb, which is consistent with the genome survey results. How does the author know that the assembled genome is erroneous? 3. Based on the author's description, it is not clear what the size of the assembled genome from a single chain using PacBio sequencing is. The author needs to provide this data in the results. 4. The authors performed quality assessments of the assembled genome using various methods such as Merqury. However, the description of the evaluation results is lacking. The authors are requested to include the QV evaluation values and additional results of SNP alignment for the second-generation sequencing data. 5. For gene annotation, the authors used the genomes of five species of Pleuronectidae as references. We are eager to see the results of the alignment analysis between the genome obtained using PacBio Revio and the aforementioned five fish genomes. Although these results do not need to be included in the main text, they should be provided as part of the response to the reviewers, including the alignment results and alignment rates for both sets of assembled genomes (500 Mb and 633 Mb). 6. The authors are requested to include the length information of each chromosome in the supplementary files. From the assembly results, it appears that the PacBio Revio results are not as impressive as anticipated, particularly with a Scaffold N50 of 29.4 Mbp. Is this due to limitations in the length of the chromosomes themselves, affecting the quality metrics of this genome? 7. The data should be uploaded to NCBI and obtain the corresponding registration code.

      Re-review: This study aims to perform chromosome-level genome assembly of the lemon sole (Microstomus kitt) and conduct a comprehensive analysis of its genome using high-throughput sequencing technology. Researchers utilized PacBio HiFi sequencing technology to carry out whole-genome sequencing of this species, resulting in a high-quality and complete genome sequence. The genome sequence has a length of 633 Mbp, with 23 chromosome-level sequences successfully assembled. Additionally, BUSCO analysis indicated that this genome sequence possesses a high level of completeness. These results suggest that the lemon sole genome sequence can serve as an important reference for future population genetic studies of commercially valuable edible fish species. However, there are certain issues with the paper that need to be addressed: The authors emphasize that female lemon soles grow larger than males, yet they chose to sequence the male genome instead of focusing on the more unique female. The authors should clarify this choice. The HI-C assisted assembly results show that male lemon soles have 23 chromosome pairs. Are there any heteromorphic chromosomes? The authors need to elucidate the karyotype of the lemon sole, as this information is significant for both the genome assembly and subsequent research. The survey results indicate a high level of heterozygosity in lemon sole. How did the authors account for this high heterozygosity to obtain a relatively complete genome? Could this affect the accuracy of the genome? Although the authors achieved high-quality genome results through PacBio sequencing, they used BUSCO for genome quality assessment. To further highlight the completeness and accuracy of the assembled genome, it is recommended that the authors utilize QV for additional evaluation. To ensure high levels of data sharing and reproducibility, the authors are requested to provide the chromosome-level genome fasta file and gff annotation file. In summary, the authors are encouraged to provide additional information and make necessary revisions.

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      Reply to the reviewers

      1. Response to reviewers

      We would like to thank the reviewers for carefully reading our manuscript and for their valuable comments in support for the publication of our investigation of rapid promoter evolution of accessory gland genes between Drosophila species and hybrids. We are glad to read that the reviewers find our work interesting and that it provides valuable insights into the regulation and divergence of genes through their promoters. We are encouraged by their acknowledgement of the overall quality of the work and the importance of our analyses in advancing the understanding of cis-regulatory changes in species divergence.

      2. Point-by-point description of the revisions

      Reviewer #

      Reviewer Comment

      Author Response/Revision

      Reviewer 1

      The authors test the hypothesis that promoters of genes involved in insect accessory glands evolved more rapidly than other genes in the genome. They test this using a number of computational and experimental approaches, looking at different species within the Drosophila melanogaster complex. The authors find an increased amount of sequence divergence in promoters of accessory gland proteins. They show that the expression levels of these proteins are more variable among species than randomly selected proteins. Finally, they show that within interspecific hybrids, each copy of the gene maintains its species-specific expression level.

      We thank Reviewer 1 for their detailed review and positive feedback on our manuscript, and for their helpful suggestions. We have now fully addressed the points raised by Reviewer 1 and have provided the suggested clarifications and revisions to improve the flow, readability, and presentation of the data, which we believe have improved the manuscript significantly.

      The work is done with expected standards of controls and analyses. The claims are supported by the analysis. My main criticism of the manuscript has to do not with the experiments or conclusion themselves but with the presentation. The manuscript is just not very well written, and following the logic of the arguments and results is challenging.

      The problem begins with the Abstract, which is representative of the general problems with the manuscript. The Abstract begins with general statements about the evolution of seminal fluid proteins, but then jumps to accessory glands and hybrids, without clarifying what taxon is being studied, and what hybrids they are talking about. Then, the acronym Acp is introduced without explanation. The last two sentences of the Abstract are very cumbersome and one has to reread them to understand how they link to the beginning of the Abstract.

      More generally, if this reviewer is to be seen as an "average reader" of the paper, I really struggled through reading it, and did not understand many of the arguments or rationale until the second read-through, after I had already read the bottom line. The paragraph spanning lines 71-83 is another case in point. It is composed of a series of very strongly worded sentences, almost all starting with a modifier (unexpectedly, interestingly, moreover), and supported by citations, but the logical flow doesn't work. Again, reading the paragraph after I knew where the paper was going was clearer, but on a first read, it was just a list of disjointed statements.

      Since most of the citations are from the authors' own work, I suspect they are assuming too much prior understanding on the part of the reader. I am sure that if the authors read through the manuscript again, trying to look through the eyes of an external reader, they will easily be able to improve the flow and readability of the text.

      We thank the reviewer for their detailed feedback and are glad that they acknowledge our work fully supports the claims of our manuscript. We also appreciate their helpful suggestions for improving the readability of the manuscript and have done our best to re-write the abstract and main text where indicated. In particular, the paragraph between lines 71-83 have been rewritten and we have taken care to write to non-expert readers.

      1) In the analysis of expression level differences, it is not clear what specific stage / tissue the levels taken from the literature refer to. Could it be that the source of the data is from a stage or tissue where seminar fluid proteins will be expressed with higher variability in general (not just inter-specifically) and this could be skewing the results? Please add more information on the original source of the data and provide support for their validity for this type of comparison.

      These were taken from publicly available adult male Drosophila datasets, listed in the data availability statement and throughout the manuscript. We have provided more detail on the tissue used for analysis of Acp gene expression levels.

      2) The sentence spanning lines 155-157 needs more context.

      We have added more context to lines 155-157.

      3) Line 203-204: What are multi-choice enhancers?

      We replaced the sentence with "... such as rapidly evolving enhancers or nested epistasis enhancer networks"

      4) Figure 1: The terminology the authors use, comparing the gene of interest to "Genome" is very confusing. They are not comparing to the entire genome but to all genes in the genome, which is not the same.

      We have changed the word "genome" to "all genes in the genome" on the reviewer's suggestion.

      5) Figure 2: Changes between X vs. Y is redundant (either changes between X and Y or changes in X vs. Y).

      We assume that the reviewer is referring to Fig. 2B, which does not measure changes between X and Y, but changes in distribution between Acps and the control group. We have explained this in the figure legend.

      The manuscript addresses a general question in evolutionary biology - do control regions diverge more quickly protein coding regions. The answer is that yes, they do, but this is actually not very surprising. The work is probably thus of more interest to people interested in the copulatory proteins or in the evolution of mating systems, than to people interested in broader evolutionary questions.

      We appreciate this reviewer's recognition of the significance of our work and would like to point out that there are very few studies looking at promoter evolution as detailed in the introduction. Of particular relevance, our study using Acp genes allows us to directly test the impact of promoter mutations on the expression by comparing two alleles in male accessory glands of Drosophila hybrids. Male accessory glands consist of only two secretory cell types allowing us to study evolution of gene expression in a single cell type (Acps are either expressed in main cells or secondary cells). Amid this unique experimental set up we can conclude that promoter mutations can act dominant, in contrast to mutations in protein coding regions, which are generally recessive. Thus, our study is unique in pointing out a largely overseen aspect of gene evolution.

      Reviewer 2

      This manuscript explores promoter evolution of genes encoding seminal fluid proteins expressed in the male accessory gland of Drosophila and finds cis-regulatory changes underlie expression differences between species. Although these genes evolve rapidly it appears that the coding regions rarely show signs of positive selection inferring that changes in their expression and hence promoter sequences can underlie the evolution of their roles within and among species.

      We thank Reviewer 2 for their thorough review, positive feedback on the importance of our work, and suggestions for improving the manuscript. We have addressed all points raised by the reviewer, including analysis of Acp coding region evolution, additional analyses of hybrid expression data, and improved the clarity of the text.

      Figure 1 illustrates evidence that the promoter regions of these gene have accumulated more changes than other sampled genes from the Drosophila genome. While this convinces that the region upstream of the transcription start site has diverged considerably in sequence (grey line compared to black line), Figure 1A also suggests the "Genespan" region which includes the 5'UTR but presumably also part of the coding region is also highly diverged. It would be useful to see how the pattern extends into the coding region further to compare further to the promoter region (although Fig 1H does illustrate this more convincingly).

      The reviewer raises an interesting point, and certainly all parts of genes evolve. Fig. 1A shows the evolutionary rates of Acps compared to the genome average from phyloP27way scores calculated from 27 insect species. Since these species are quite distant it is unsurprising that they show divergence in coding regions as well as promoter regions. In fact, we addressed whether promoter regions evolve fast in closely related Drosophila species in Fig. 1H compared to coding regions. We have included an additional analysis of coding region evolution in Figure 1B.

      Figure 2 presents evidence for significant changes in (presumably levels of) expression of male accessory gland protein (AcP) genes and ribosomal proteins genes between pairs of species, which is reflected in the skew of expression compared to randomly selected genes.

      Correct, we have rephrased the statement for clarity.

      Figure 3 shows detailed analysis for 3 selected AcP genes with significantly diverged expression. The authors claim this shows 'substitution' hotspots in the promoter regions of all 3 genes but this could be better illustrated by extending the plots in B-D further upstream and downstream to compare to these regions.

      We picked the 300-nucleotide promoter region for this analysis as it accumulated significant changes as shown in Fig. 1E-H, and extending the G plots (Fig. 3B-D) to regions with lower numbers of sequence changes would not substantially change the conclusion. Specifically, this analysis identifies sequence change hotspots within fast-evolving promoter regions, rather than comparing promoter regions to other genomic regions, as we previously addressed. The plot is based on a cumulative distribution function and the significant positive slope in the upstream region where promoters are located identifies a hotspot for accumulation of substitutions. There could be other hotspots, but the point being made is that significant hotspots consistently appear in the promoter region of these three genes.

      Figure 4 shows the results of expression analysis in parental lines of each pair of species and F1 hybrids. However the results are very difficult to follow in the figure and in the relevant text. While the schemes in A, C. E and G are helpful, the gel images are not the best quality and interpretations confusing. An additional scheme is needed to illustrate hypothetical outcomes of trans change, cis change and transvection to help interpret the gels. On line 169 (presumably referring to panels D and F although C and D are cited on the next line) the authors claim that Obp56f and CG11598 'were more expressed in D. melanogaster compared to D. simulans' but in the gel image the D. sim band is stronger for both genes (like D. sechellia) compared to the D. mel band. The authors also claim that the patterns of expression seen in the F1s are dominant for one allele and that this must be because of transvection. I agree this experiment is evidence for cis-regulatory change. However the interpretation that it is caused by transvection needs more explanation/justification and how do the authors rule out that it is not a cis X trans interaction between the species promoter differences and differences in the transcription factors of each species in the F1? Also my understanding is that transvection is relatively rare and yet the authors claim this is the explanation for 2/4 genes tested.

      We appreciate the reviewer's comments on Figure 4 and the opportunity to improve its clarity. To address these concerns, we have carefully checked the figure citations and corrected any inconsistencies.

      The reviewer raises an important point about our interpretation of transvection. We have expanded our discussion of this result to consider why transvection is a plausible explanation for the observed dominance patterns and also consider cis x trans interactions between species-specific promoters and transcription factor binding. While rare, transvection likely has more relevance in hybrid regulatory contexts involving homologous chromosome pairing which we discuss this in the revised text.

      Line 112 states that the melanogaster subgroup contains 5 species - this is incorrect - while this study looked at 5 species there are more species in this subgroup such as mauritiana and santomea.

      We have corrected the statement about the number of species in the melanogaster subgroup.

      Lines 131-134 could explain better what the conservation scores and their groupings mean and the rationale for this approach.

      We have clarified what the conservation scores and their groupings mean and the rationale for this approach.

      Line 162 - the meaning of the sentence starting on this line is unclear - it sounds very circular.

      We have rephrased the statement for more clarity.

      Line 168 should cite Fig 4 H instead of F.

      We have amended citation of Fig 4F to H.

      Reviewer 3

      In this study, McQuarrie et al. investigate the evolution of promoters of genes encoding accessory gland proteins (Acps) in species within the D. melanogaster subgroup. Using computational analyses and available genomic and transcriptomic datasets, they demonstrate that promoter regions of Acp genes are highly diverse compared to the promoters of other genes in the genome. They further show that this diversification correlates with changes in gene expression levels between closely related species. Complementing these computational analyses, the authors conduct experiments to test whether differences in expression levels of four Acp genes with highly diverged promoter regions are maintained in hybrids of closely related species. They find that while two Acp genes maintain their expression level differences in hybrids, the other two exhibit dominance of one allele. The authors attribute these findings to transvection. Based on their data, they conclude that rapid evolution of Acp gene promoters, rather than changes in trans, drives changes in Acp gene expression that contribute to speciation.

      We thank Reviewer 3 for their thorough review and suggestions. We further thank the reviewer for acknowledging the importance of our findings and for pointing out that it contributes to our understanding of speciation. We have thoroughly addressed all comments from the reviewer and significantly revised the manuscript. We believe that this has greatly improved the manuscript.

      Unfortunately, the presented data are not sufficient to fully support the conclusions. While many of the concerns can be addressed by revising the text to moderate the claims and acknowledge the methodological limitations, some key experiments require repetition with more controls, biological replicates, and statistical analyses to validate the findings.

      Specifically, some of the main conclusions heavily rely on the RT-PCR experiments presented in Figure 4, which analyze the expression of four Acp genes in hybrid flies. The authors use PCR and RFLP to distinguish species-specific alleles but draw quantitative conclusions from what is essentially a qualitative experiment. There are several issues with this approach. First, the experiment includes only two biological replicates per sample, which is inadequate for robust statistical analysis. Second, the authors did not measure the intensity of the gel fragments, making it impossible to quantify allele-specific expression accurately. Third, no control genes were used as standards to ensure the comparability of samples.

      The gold standard for quantifying allele-specific expression is using real-time PCR methods such as TaqMan assays, which allow precise SNP genotyping. To address this major limitation, the authors should ideally repeat the experiments using allele-specific real-time PCR assays. This would provide a reliable and quantitative measurement of allele-specific expression.

      If the authors cannot implement real-time PCR, an alternative (though less rigorous) approach would be to continue using their current method with the following adjustments:

      • Include a housekeeping gene in the analysis as an internal control (this would require identifying a region distinguishable by RFLP in the control).

      • Quantify the intensity of the PCR products on the gel relative to the internal standard, ensuring proper normalization.

      • Increase the sample size to allow for robust statistical analysis.

      These experiments could be conducted relatively quickly and would significantly enhance the validity of the study's conclusions.

      We thank the reviewer for their detailed suggestions for improving the conclusions in Fig. 4. Indeed, incorporating a housekeeping gene as a control supports our results for qualitative analysis of gene expression in hybrids assessing each allele individually (Fig 4), and improves interpretation for non-experts. We have also included an additional analysis in the new Fig. 5 which analyses RNA-seq expression changes in D. melanogaster x D. simulans hybrid male accessory glands. We believe these additions have significantly improved the manuscript and its conclusions.

      While the following comments are not necessarily minor, they can be addressed through revisions to the text without requiring additional experimental work. Some comments are more conceptual in nature, while others concern the interpretation and presentation of the experimental results. They are provided in no particular order.

      1. A key limitation of this study is the use of RNA-seq datasets from whole adult flies for interspecies gene expression comparisons. Whole-body RNA-seq inherently averages gene expression across all tissues, potentially masking tissue-specific expression differences. While Acp genes are likely restricted to accessory glands, the non-Acp genes and the random gene sets used in the analysis may have broader expression profiles. As a result, their expression might be conserved in certain tissues while diverging in others- an aspect that whole-body RNA-seq cannot capture. The authors should acknowledge that tissue-specific RNA-seq analyses could provide a more precise understanding of expression divergence and potentially reveal reduced conservation when considering specific tissues independently.

      We have added a section discussing the limitations in gene expression analysis in the discussion. In addition, we have included an additional Figure analysing gene expression in hybrid male accessory glands (Fig. 5).

      1. The statement in line 128, "Consistent with this model," does not accurately reflect the findings presented in Figures 2A and B. Specifically, the data in Figure 2A show that Acp gene expression divergence is significantly different from the divergence of non-Acp genes or a random sample only in the comparison between D. melanogaster and D. simulans. However, when these species are compared to D. yakuba, Acp gene expression divergence aligns with the divergence patterns of non-Acp genes or random samples. In contrast, Figure 2B shows that the distribution of expression changes is skewed for Acp genes compared to random control samples when D. melanogaster or D. simulans are compared to D. yakuba. However, this skew is absent when the two D. melanogaster and D. simulans are compared. Therefore, the statement in line 128 should be revised to accurately reflect these nuanced results and the trends shown in Figure 2A and B.

      We have updated the statement for clarity. Here, the percentage of Acps showing significant gene expression changes is greater between more closely related species, but the distribution of expression changes increases between more distantly related species.

      1. The statement in lines 136-138, "Acps were enriched for significant expression changes in the faster evolving group across all species," while accurate, overlooks a key observation. This trend was also observed in other groups, including those with slower evolving promoters, in some of the species' comparisons. Therefore, the enrichment is not unique to Acps with rapidly evolving promoters, and this should be explicitly acknowledged in the text.

      This is a valid point, and we have updated this statement as suggested.

      1. It would be helpful for the authors to explain the meaning of the d score at the beginning of the paragraph starting in line 131, to ensure clarity for readers unfamiliar with this metric.

      This scoring method is described in the methods sections, and we have now included reference to thorough explanation of how d was calculated at the indicated section.

      1. In Figure 2C-E - the title of the Y-axis does not match the text. If it represents the percentage of genes with significant expression changes, as in Figure 2A, the discrepancies between the percentages in this figure and those in Figure 2A need to be addressed.

      We have updated the method used to categorise significant changes in gene expression in the text and the figure legend for clarity.

      1. The experiment in Figure 3 needs a better explanation in the text. What is the analysis presented in Figure 3B-D. How many species were compared?

      We have added additional details in the results section and an explanation of how sequence change hotspots were calculated in the results section is available.

      1. The concept of transvection should be omitted from this manuscript. First, the definition provided by the authors is inaccurate. Second, even if additional experiments were to convincingly show that one allele in hybrid animals is dominant over the other, there are alternative explanations for this phenomenon that do not involve transvection. The authors may propose transvection as a potential model in the discussion, but they should do so cautiously and explicitly acknowledge the possibility of other mechanisms.

      We have updated the text to more conservatively discuss transvection, moving this to the discussion section with additional possibilities discussed.

      1. The statement at the end of the introduction is overly strong and would benefit from more cautious phrasing. For instance, it could be reworded as: "These findings suggest that promoter changes, rather than genomic background, play a significant role in driving expression changes, indicating that promoter evolution may contribute to the rise of new species."

      We have reworded this line following the reviewer's suggestion.

      1. Line 32 of the abstract: The term "Acp" is introduced without explaining what it stands for. Please define it as "Accessory gland proteins (Acp)" when it first appears.

      We have updated the manuscript to define Acp where it is first mentioned.

      1. Line 61: The phrase "...through relaxed,..." is unclear. Specify what is relaxed (e.g., "relaxed selective pressures").

      We have included description of relaxed selective pressures.

      1. The sentence in lines 74-76, starting in "Interestingly,...." Needs revision for clarity.

      We have removed the word interestingly.

      1. Line 112: Revise "we focused on the melanogaster subgroup which is made up of five species" to: "we focused on the melanogaster subgroup, which includes five species."

      We have made this change in the text.

      1. In line 144 use the phrase "promoter conservation" instead of "promoter evolution"

      We have updated the phrasing.

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      Referee #3

      Evidence, reproducibility and clarity

      Summary:

      In this study, McQuarrie et al. investigate the evolution of promoters of genes encoding accessory gland proteins (Acps) in species within the D. melanogaster subgroup. Using computational analyses and available genomic and transcriptomic datasets, they demonstrate that promoter regions of Acp genes are highly diverse compared to the promoters of other genes in the genome. They further show that this diversification correlates with changes in gene expression levels between closely related species. Complementing these computational analyses, the authors conduct experiments to test whether differences in expression levels of four Acp genes with highly diverged promoter regions are maintained in hybrids of closely related species. They find that while two Acp genes maintain their expression level differences in hybrids, the other two exhibit dominance of one allele. The authors attribute these findings to transvection. Based on their data, they conclude that rapid evolution of Acp gene promoters, rather than changes in trans, drives changes in Acp gene expression that contribute to speciation.

      Major comments:

      Unfortunately, the presented data are not sufficient to fully support the conclusions. While many of the concerns can be addressed by revising the text to moderate the claims and acknowledge the methodological limitations, some key experiments require repetition with more controls, biological replicates, and statistical analyses to validate the findings.

      Specifically, some of the main conclusions heavily rely on the RT-PCR experiments presented in Figure 4, which analyze the expression of four Acp genes in hybrid flies. The authors use PCR and RFLP to distinguish species-specific alleles but draw quantitative conclusions from what is essentially a qualitative experiment. There are several issues with this approach. First, the experiment includes only two biological replicates per sample, which is inadequate for robust statistical analysis. Second, the authors did not measure the intensity of the gel fragments, making it impossible to quantify allele-specific expression accurately. Third, no control genes were used as standards to ensure the comparability of samples.

      The gold standard for quantifying allele-specific expression is using real-time PCR methods such as TaqMan assays, which allow precise SNP genotyping. To address this major limitation, the authors should ideally repeat the experiments using allele-specific real-time PCR assays. This would provide a reliable and quantitative measurement of allele-specific expression.

      If the authors cannot implement real-time PCR, an alternative (though less rigorous) approach would be to continue using their current method with the following adjustments:

      • Include a housekeeping gene in the analysis as an internal control (this would require identifying a region distinguishable by RFLP in the control).
      • Quantify the intensity of the PCR products on the gel relative to the internal standard, ensuring proper normalization.
      • Increase the sample size to allow for robust statistical analysis. These experiments could be conducted relatively quickly and would significantly enhance the validity of the study's conclusions.

      Minor comments

      While the following comments are not necessarily minor, they can be addressed through revisions to the text without requiring additional experimental work. Some comments are more conceptual in nature, while others concern the interpretation and presentation of the experimental results. They are provided in no particular order. 1. A key limitation of this study is the use of RNA-seq datasets from whole adult flies for interspecies gene expression comparisons. Whole-body RNA-seq inherently averages gene expression across all tissues, potentially masking tissue-specific expression differences. While Acp genes are likely restricted to accessory glands, the non-Acp genes and the random gene sets used in the analysis may have broader expression profiles. As a result, their expression might be conserved in certain tissues while diverging in others- an aspect that whole-body RNA-seq cannot capture. The authors should acknowledge that tissue-specific RNA-seq analyses could provide a more precise understanding of expression divergence and potentially reveal reduced conservation when considering specific tissues independently. 2. The statement in line 128, "Consistent with this model," does not accurately reflect the findings presented in Figures 2A and B. Specifically, the data in Figure 2A show that Acp gene expression divergence is significantly different from the divergence of non-Acp genes or a random sample only in the comparison between D. melanogaster and D. simulans. However, when these species are compared to D. yakuba, Acp gene expression divergence aligns with the divergence patterns of non-Acp genes or random samples. In contrast, Figure 2B shows that the distribution of expression changes is skewed for Acp genes compared to random control samples when D. melanogaster or D. simulans are compared to D. yakuba. However, this skew is absent when the two D. melanogaster and D. simulans are compared. Therefore, the statement in line 128 should be revised to accurately reflect these nuanced results and the trends shown in Figure 2A and B. 3. The statement in lines 136-138, "Acps were enriched for significant expression changes in the faster evolving group across all species," while accurate, overlooks a key observation. This trend was also observed in other groups, including those with slower evolving promoters, in some of the species' comparisons. Therefore, the enrichment is not unique to Acps with rapidly evolving promoters, and this should be explicitly acknowledged in the text. 4. It would be helpful for the authors to explain the meaning of the d score at the beginning of the paragraph starting in line 131, to ensure clarity for readers unfamiliar with this metric. 5. In Figure 2C-E - the title of the Y-axis does not match the text. If it represents the percentage of genes with significant expression changes, as in Figure 2A, the discrepancies between the percentages in this figure and those in Figure 2A need to be addressed. 6. The experiment in Figure 3 needs a better explanation in the text. What is the analysis presented in Figure 3B-D. How many species were compared? 7. The concept of transvection should be omitted from this manuscript. First, the definition provided by the authors is inaccurate. Second, even if additional experiments were to convincingly show that one allele in hybrid animals is dominant over the other, there are alternative explanations for this phenomenon that do not involve transvection. The authors may propose transvection as a potential model in the discussion, but they should do so cautiously and explicitly acknowledge the possibility of other mechanisms. 8. The statement at the end of the introduction is overly strong and would benefit from more cautious phrasing. For instance, it could be reworded as: "These findings suggest that promoter changes, rather than genomic background, play a significant role in driving expression changes, indicating that promoter evolution may contribute to the rise of new species."

      Text edits:

      Throughout the manuscripts there are incomplete sentences and sentences that are not clear. Below is a list of corrections:

      1. Line 32 of the abstract: The term "Acp" is introduced without explaining what it stands for. Please define it as "Accessory gland proteins (Acp)" when it first appears.
      2. Line 61: The phrase "...through relaxed,..." is unclear. Specify what is relaxed (e.g., "relaxed selective pressures").
      3. The sentence in lines 74-76, starting in "Interestingly,...." Needs revision for clarity.
      4. Line 112: Revise "we focused on the melanogaster subgroup which is made up of five species" to: "we focused on the melanogaster subgroup, which includes five species."
      5. In line 144 use the phrase "promoter conservation" instead of "promoter evolution"

      Significance

      This study addresses an important question in evolutionary biology: how seminal fluid proteins achieve rapid evolution despite showing limited adaptive changes in their coding regions. By focusing on accessory gland proteins (Acps) and examining their promoter regions, the authors suggest promoter-driven evolution as a potential mechanism for rapid seminal fluid protein diversification. While this hypothesis is intriguing and can contribute to our understanding of speciation, more rigorous analysis and experimental validation would be needed to support the conclusions. The revised manuscript can be of interest to fly geneticists and to scientists in the fields of gene regulation and evolution.

      Keywords for my expertise: Enhancers, transcriptional regulation, development, evolution, Drosophila.

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      Referee #2

      Evidence, reproducibility and clarity

      Summary

      This manuscript explores promoter evolution of genes encoding seminal fluid proteins expressed in the male accessory gland of Drosophila and finds cis-regulatory changes underlie expression differences between species. Although these genes evolve rapidly it appears that the coding regions rarely show signs of positive selection inferring that changes in their expression and hence promoter sequences can underlie the evolution of their roles within and among species.

      Major comments

      Figure 1 illustrates evidence that the promoter regions of these gene have accumulated more changes than other sampled genes from the Drosophila genome. While this convinces that the region upstream of the transcription start site has diverged considerably in sequence (grey line compared to black line), Figure 1A also suggests the "Genespan" region which includes the 5'UTR but presumably also part of the coding region is also highly diverged. It would be useful to see how the pattern extends into the coding region further to compare further to the promoter region (although Fig 1H does illustrate this more convincingly).

      Figure 2 presents evidence for significant changes in (presumably levels of) expression of male accessory gland protein (AcP) genes and ribosomal proteins genes between pairs of species, which is reflected in the skew of expression compared to randomly selected genes.

      Figure 3 shows detailed analysis for 3 selected AcP genes with significantly diverged expression. The authors claim this shows 'substitution' hotspots in the promoter regions of all 3 genes but this could be better illustrated by extending the plots in B-D further upstream and downstream to compare to these regions.

      Figure 4 shows the results of expression analysis in parental lines of each pair of species and F1 hybrids. However the results are very difficult to follow in the figure and in the relevant text. While the schemes in A, C. E and G are helpful, the gel images are not the best quality and interpretations confusing. An additional scheme is needed to illustrate hypothetical outcomes of trans change, cis change and transvection to help interpret the gels. On line 169 (presumably referring to panels D and F although C and D are cited on the next line) the authors claim that Obp56f and CG11598 'were more expressed in D. melanogaster compared to D. simulans' but in the gel image the D. sim band is stronger for both genes (like D. sechellia) compared to the D. mel band. The authors also claim that the patterns of expression seen in the F1s are dominant for one allele and that this must be because of transvection. I agree this experiment is evidence for cis-regulatory change. However the interpretation that it is caused by transvection needs more explanation/justification and how do the authors rule out that it is not a cis X trans interaction between the species promoter differences and differences in the transcription factors of each species in the F1? Also my understanding is that transvection is relatively rare and yet the authors claim this is the explanation for 2/4 genes tested.

      Minor comments

      Line 112 states that the melanogaster subgroup contains 5 species - this is incorrect - while this study looked at 5 species there are more species in this subgroup such as mauritiana and santomea.

      Lines 131-134 could explain better what the conservation scores and their groupings mean and the rationale for this approach.

      Line 162 - the meaning of the sentence starting on this line is unclear - it sounds very circular.

      Line 168 should cite Fig 4 H instead of F.

      Significance

      This paper is generally well written although some sections would benefit from more explanation. The paper demonstrates cis-regulatory changes between the promoters of orthologs of male accessory gland genes underlie expression differences but that the species differences are not always reflected in hybrids, which the authors interpret as being caused by transvection although there could be other explanations. Overall this provides new insights into the regulation and divergence of these interesting genes. The paper does not explore the consequences of these changes in gene expression although this is discussed to some extent in the Discussion section.

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      Referee #1

      Evidence, reproducibility and clarity

      The authors test the hypothesis that promoters of genes involved in insect accessory glands evolved more rapidly than other genes in the genome. They test this using a number of computational and experimental approaches, looking at different species within the Drosophila melanogaster complex. The authors find an increased amount of sequence divergence in promoters of accessory gland proteins. They show that the expression levels of these proteins are more variable among species than randomly selected proteins. Finally, they show that within interspecific hybrids, each copy of the gene maintains its species-specific expression level.

      The work is done with expected standards of controls and analyses. The claims are supported by the analysis. My main criticism of the manuscript has to do not with the experiments or conclusion themselves but with the presentation. The manuscript is just not very well written, and following the logic of the arguments and results is challenging. The problem begins with the Abstract, which is representative of the general problems with the manuscript. The Abstract begins with general statements about the evolution of seminal fluid proteins, but then jumps to accessory glands and hybrids, without clarifying what taxon is being studied, and what hybrids they are talking about. Then, the acronym Acp is introduced without explanation. The last two sentences of the Abstract are very cumbersome and one has to reread them to understand how they link to the beginning of the Abstract.

      More generally, if this reviewer is to be seen as an "average reader" of the paper, I really struggled through reading it, and did not understand many of the arguments or rationale until the second read-through, after I had already read the bottom line. The paragraph spanning lines 71-83 is another case in point. It is composed of a series of very strongly worded sentences, almost all starting with a modifier (unexpectedly, interestingly, moreover), and supported by citations, but the logical flow doesn't work. Again, reading the paragraph after I knew where the paper was going was clearer, but on a first read, it was just a list of disjointed statements.

      Since most of the citations are from the authors' own work, I suspect they are assuming too much prior understanding on the part of the reader. I am sure that if the authors read through the manuscript again, trying to look through the eyes of an external reader, they will easily be able to improve the flow and readability of the text.

      More specific comments:

      1. In the analysis of expression level differences, it is not clear what specific stage / tissue the levels taken from the literature refer to. Could it be that the source of the data is from a stage or tissue where seminar fluid proteins will be expressed with higher variability in general (not just inter-specifically) and this could be skewing the results? Please add more information on the original source of the data and provide support for their validity for this type of comparison.
      2. The sentence spanning lines 155-157 needs more context.
      3. Line 203-204: What are multi-choice enhancers?
      4. Figure 1: The terminology the authors use, comparing the gene of interest to "Genome" is very confusing. They are not comparing to the entire genome but to all genes in the genome, which is not the same.
      5. Figure 2: Changes between X vs. Y is redundant (either changes between X and Y or changes in X vs. Y).

      Significance

      The manuscript addresses a general question in evolutionary biology - do control regions diverge more quickly protein coding regions. The answer is that yes, they do, but this is actually not very surprising. The work is probably thus of more interest to people interested in the copulatory proteins or in the evolution of mating systems, than to people interested in broader evolutionary questions.

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      Reply to the reviewers

      1. Reviewer #1 Evidence, reproducibility and clarity:

        Summary:

      In this manuscript, authors demonstrated the role of ECM-dependent MEK/ERK/MITF signaling pathway that influences the plasticity of MCs (melanocytes) through their interactions with the environment. The findings emphasize the essential role of the extracellular matrix (ECM) in controlling MC function and differentiation, highlighting a critical need for further research to understand the complex interactions between mechanical factors and ECM components in the cellular microenvironment. Overall, the manuscript is concise, written well and shed light on a complex relationship between ECM protein types and substrate stiffness that affects MC mechanosensation. However, understanding detailed molecular mechanisms involved, especially the roles of MITF and other key regulators, is crucial for comprehending MC function and related pathologies. Authors need to clarify some minor queries to be considered for publication.

      We thank this reviewer for the time and caution taken to assess our work. To provide a better understanding of the molecular mechanisms involved in MITF modulation and MC function in response to ECM proteins, we substantially revised the manuscript and now included e.g. bulk RNA sequencing, pharmacological inhibition of FAK and ERK (in addition to MEK inhibition), and MITF depletion.

      Major comments to the Authors:

        • Authors have chosen ERK signaling pathways to test and draw their conclusion based on existing knowledge in the field, as several studies previously reported the role of ECM to modulate the ERK signaling pathway but it would be interesting to test other signaling pathways unbiasedly; e.g. ECM can also regulate Wnt signaling (PMID: 29454361) and connection of MITF and its target gene TYR expression is also regulated by Wnt in context of melanocyte. (PMID: 29454361, PMID: 34878101, PMID: 38020918).*

      The new transcriptome analysis (line 258 ff., revised fig. 5, new fig. 6, new suppl. fig. S5) indeed showed that some components of the Wnt signaling pathway are differentially expressed in response to ECM proteins (new fig. 6B). In comparison, however, the expression of genes involved in MAPK/ERK signaling was more prominently affected by the specific ECM types (new fig. 6C, D), congruent with the biochemical results we presented in the original manuscript. We therefore focused our mechanistic analyses on this pathway, and we consolidated our initial findings with additional pharmacological inhibition experiments. Specifically, like MEK inhibition, ERK inhibition (new fig. 6J-L) increased both MITF nuclear localization and melanin production in MCs exposed to FN, reinforcing the relevance of this pathway in control of MC functions in the model used.

      We agree that an additional contribution of Wnt signaling to ECM-dependent regulation of MC phenotypes is possible, including Mitf and Tyr expression. Next to the new Wnt-related transcriptome data (line 323 ff., new fig. 6B), we therefore now included a short discussion on that aspect (line 478 ff.). However, we feel that a comprehensive comparison of the individual contributions of Wnt vs. ERK signaling is beyond the scope of the current manuscript.

      • Discussion line 340-344. Please provide the data as it is directly connected to the study, and it would be crucial to interpret data better. As FAK is upregulated and FAK inhibitor did not reduce pERK, is there any possibility that other kinases might involve. Please discuss. Again, authors should check Wnt activation as FAK can activate Wnt signaling in response to matrix stiffness as well. (PMID 29454361).*

      We agree with the reviewer that the FAK data required further investigation. In the revised version, we re-examined the potential role of FAK as an upstream regulator of ERK activation using the FAK inhibitor Ifebemtinib, rather than Defactinib as used in our original experiments. Our previous conclusion-that ERK activation was independent of FAK-was likely influenced by limitations associated with Defactinib, which did not properly reduce p-FAK levels despite lowering focal adhesion numbers, accompanied with an increase of ERK phosphorylation alongside a decrease of nuclear MITF levels. In contrast, Ifebemtinib treatment led to a more effective inhibition of FAK, as evidenced by a marked reduction in both p-FAK levels and focal adhesion number (new suppl. fig. 6B,C). Importantly, this was accompanied by a significant decrease in p-ERK levels (new fig. 6M,N), suggesting that FAK contributes to ERK activation in response to ECM molecules in our model. Furthermore, FAK inhibition similar to MEK and ERK inhibition, led to increased melanin production in MCs cultured on FN (new fig. 6O). These new data are now included in the revised version of the manuscript (line 360 ff., new fig. 6M-O, new suppl. fig. 6).

      Nonetheless, this does not exclude the possibility that additional kinases and pathways, including Wnt signaling, may also be involved. We acknowledge this possibility in the revised discussion (lines 478-488).

      • Rationale for selecting MITF for the study is very weak. Please justify in the discussion why authors have chosen to study MITF/ERK axis with a more logistic approach.*

      We have focused central aspects of our analyses on MITF because it is a central regulator of MC differentiation, pigmentation, and survival, and its activity has previously been reported to be modulated by ERK. Considering the observed changes in pigmentation, proliferation, and gene expression in response to distinct ECM molecules, we hypothesized that MITF acts as a key integrator of these ECM-dependent signals. Our data indeed support this rationale: we detected ECM-type-dependent MITF levels and localization, and manipulating the ERK pathway altered MITF activity and associated functional outputs. Moreover, siRNA-mediated downregulation of MITF in MCs cultured on COL I led to a marked reduction in melanin content (revised fig. 4D). Together, these data emphasize that the ERK/MITF axis serves as a pathway that responds to extracellular cues and links these to MC behavior. For clarity, we have included an additional explanation on our rationale in the revised manuscript (lines 146-152).

      • It is suggested to check for the changes in the transcriptomic profile of melanocytes upon culturing on different matrix to get a more comprehensive view associated with the molecular mechanisms involved.*

      We fully agree with the reviewer on the importance of assessing the ECM-dependent transcriptomes of MCs. Therefore, we have now performed RNA sequencing to compare the transcriptomic profiles of MCs cultured on COL IV-, COL I- and FN-coated stiff substrates (line 258 ff. and revised fig. 5, new fig. 6, new suppl. fig. S5). This analysis provided a broader view of the molecular responses of MCs to ECM molecules and complemented our previous molecular and phenotypes analyses. The obtained transcriptomes confirmed significant modulation of genes associated with MC differentiation and pigmentation, as well as genes involved in signaling pathways such as MAPK/ERK and Wnt (see also answers to points 1-3). These findings help contextualize the ECM-dependent phenotypic changes and strengthen the mechanistic insights presented in the study.

      • Please provide the protein expression of genes involved in cell cycle progression and/or apoptosis to support the data in Fig. 3D-E.*

      To support the observations presented in original fig. 3, we employed immunostaining to assess the protein expression of Ki67, which is both a well-established marker and a protein involved in cell cycle progression (PMID: 28630280). In revised figure 3E, a significant reduction in the proportion of Ki67-positive cells on FN compared to COL I was observed, reinforcing our initial findings derived from BrdU incorporation assays and direct microscopic monitoring of cell division (revised fig. 3D,F).

      In addition, global gene expression analysis revealed differentially expressed genes related to cell cycle regulation and apoptosis (revised fig. 5C,D), in line with the reduced proliferation observed. Notably, FN also triggered the differential expression of genes associated with cellular senescence (revised fig. 5E). Together, these data suggest that adhesion to FN induces a transcriptional and phenotypic shift in MCs toward a less-proliferative state that is associated with differential cell cycle modulation and signs of senescence.

      Minor comment to the Authors:

        • Discussion line 358-359, using term synergy is an overstatement as the collective data do not support the claim. Very little role of matrix stiffness is demonstrated by experimental data.*

      We thank the reviewer for this comment and agree that the term "synergy" may overstate the conclusions drawn from the current dataset. We have therefore removed this term from the revised version of the manuscript to more accurately reflect the data.

      • Method section, BrdU assay and BrdU assay-cell proliferation can be combined in method section.*

      We have combined the descriptions of the BrdU assay and BrdU-based cell proliferation assay into a single, unified section in the Methods.

      • What trigger melanocytes to respond to different microenvironment. Please discuss.*

      To address this question, we have added the following paragraph to the Discussion (lines 377-380): "Our study identifies ECM components as critical environmental triggers that instruct MC behavior. Through dynamic interactions with the ECM, MCs engage adhesion-dependent signaling pathways, such as FAK activation, enabling them to decode contextual ECM inputs and adapt their phenotype accordingly."

      • Fig 3C and 5D Tyr mRNA expression is tested. Authors should also test for the protein expression in the similar set of studies.*

      We thank the reviewer for this suggestion and agree that assessing TYR protein expression would be valuable. However, we have encountered difficulties with the currently available antibodies and detection methods, which in our hands appeared unreliable for consistently detecting endogenous TYR protein levels in MCs under these conditions. For this reason, we relied on Tyr mRNA expression as a robust and reproducible readout and complemented this with functional assays such as melanin content measurement as a read-out that indirectly reflects TYR enzymatic activity. Of note, our transcriptomic analysis also revealed Tyr and other melanogenesis genes as differentially expressed genes when comparing MCs grown on COLI vs FN (revised fig. 5A,B).

      • Line 217-218, Authors claim stiffness mediated increase of MITF nuclear localization in Col I, however Fig. 4A-B does not represent that claim. Please justify.*

      Fig. 4A shows representative images of MCs cultured on stiff substrates coated with different ECM types, while the original figure 4B included the comparison across substrate stiffnesses for each ECM condition. We have now generated additional datasets to assess global MITF levels as well as nuclear localization across stiffness conditions in the presence of the different ECM types, demonstrating that nuclear MITF is significantly higher in cells cultured on stiff vs. soft or intermediate stiffness (revised fig. 4B,C). Of note, we do not detect a significant difference between soft and intermediate substrate stiffness, which could hint to a threshold of MITF dynamics in stiffness sensitivity. We have updated the figure legend and corresponding text to ensure the data presentation accurately supports our conclusions.

      Significance:

      Overall, the study is well-planned, the experiments are well-designed and executed with appropriate use of statistical analysis. However, a more in-depth analysis of the molecular mechanisms is necessary to clarify how the extracellular matrix (ECM) regulates ERK or MITF nuclear translocation.

      We agree and feel that the additional data in the revised manuscript that explored transcriptional changes and the FAK/MEK/ERK/MITF axis in response to ECM proteins provide improved insights into ECM-mediated regulation of ERK and MC pigmentation.

      This study enhances our existing knowledge by linking the well-established role of the extracellular matrix (ECM) in regulating ERK signaling to ERK's involvement in controlling MITF, a key regulator of melanocyte differentiation. It further establishes the ECM's role in controlling melanocyte function and differentiation.

      This study will interest readers working in the field of the tumor microenvironment, as it explores the role of the extracellular matrix and its complexity and stiffness in disease progression, not only in melanoma but also in other types of cancer.

      1. Reviewer #2 Evidence, reproducibility and clarity:

      Summary:

      In their manuscript, Luthold et al describe the behaviour of immortalized mouse melanocytes cultured on various extracellular matrix (ECM) proteins and substrates of different stiffness. They found that fibronectin, collagen IV and collagen I have different effects on melanocyte morphology, migration, and proliferation. They further link these differential effects to MITF localization and MEK/ERK signalling. This work shows that fibronectin supports melanocyte migration, which was associated with a dendritic morphology and correlated with increased MEK/ERK signalling and decreased MITF nuclear localization. In contrast, collagen I promoted melanocyte proliferation with low MEK/ERK signalling, enhanced MITF nuclear localization and high melanin production.

      While this study is well designed and the data adequately presented and interpreted, the impact of its conclusions is limited by the incomplete mechanistic characterization of the observed phenotypes and by the lack of parallels with physiological conditions. To strengthen their manuscript, the authors should consider the following comments:

      We also wish to thank this reviewer for the efforts made to assess our work and help us improve the study. We substantially revised the manuscript and now included e.g. bulk RNA sequencing and various loss-of-function approaches to better delineate the signaling pathways involved in ECM-dependent control of MCs.

      Major comments to the Authors:

        • Characterization of observed phenotypes:*
      • *The link between matrix-sensing and intracellular signalling is missing. Which types of integrins are expressed by iMCs? *

      This is indeed an interesting point. Our RNA sequencing analysis indicates that MCs express integrins known to mediate adhesion to COL I and FN, including Itga2, Itga3, Itga5, Itgav, Itgb1, and Itgb3 (revised fig. 5K). Importantly, the expression of these integrins remains relatively consistent across ECM conditions (COL I, COL IV, and FN), suggesting that the phenotypic differences observed may not be directly explained by variations in integrin expression.

      • Are any of these integrins required for the observed phenotypes?

      To assess a functional involvement, we conducted a pilot experiment blocking β1-integrin in MCs seeded on COL I and observed a marked reduction in MC adhesion (see associated graph 1, provided to this reviewer). However, the compromised cell spreading and resulting widespread detachment introduced confounding effects, making it difficult to interpret downstream events such as MITF nuclear localization. Since such readouts can be indirectly influenced by the overall adhesion state and associated signaling pathways such as FAK, we chose not to pursue further mechanistic analysis using this approach. Targeted strategies (e.g., inducible knockdown, acute protein degradation) will be needed in the future to dissect the precise role of individual integrins in mediating ECM-specific signaling responses in MCs.

      Graph 1: Effect of β1-integrin blocking on MC adhesion. iMCs were detached using PBS-EDTA (10 min, 37 {degree sign}C) and incubated for 15 min on ice with either 10 μg/mL β1-integrin-blocking antibody (CD29, clone TS2/16; Invitrogen, #AB_1210468) or 10 μg/mL IgG isotype control. Cells (5,000 per well) were then seeded on COL I-coated substrates. After 1 h, non-adherent cells were gently washed off with PBS, and adherent cells were fixed with 4% PFA. Cell adhesion was quantified by counting the number of attached cells per µm² under a microscope.

      • The phenotypic changes described here are interesting but only partially analysed. Transcriptomic studies would yield a more complete view of cell state transitions (optional). At a minimum, could the authors detect any changes in cadherin expression, or in other genes classically involved in phenotype switching, such as twist1, snail or zeb1?

      We thank the reviewer for this important suggestion, which helped to improve this manuscript. We have now performed bulk RNA sequencing to analyze global gene expression changes in MCs cultured on different ECM substrates (revised fig. 5, new suppl. fig. 5). Among these, we explored gene expression programs associated with MC plasticity and differentiation (revised fig. 5F-H): MCs cultured on FN exhibited reduced expression of melanocytic differentiation markers and upregulation of genes linked to plasticity, dedifferentiation, and neural crest-like features, suggesting a shift toward a less differentiated state, reflecting aspects of a phenotypic switch.

      Nonetheless, as part of this analysis (but not included in the manuscript), we found that Zeb2, Snai2, and Zeb1 were expressed at similar levels across ECM conditions. Similarly, among the cadherins, Cdh1 and Cdh2 were not differentially expressed, albeit the overall low expression of Cdh1 showed a trend towards a reduction on COL I. Finally, Snai1, Twist1, and Twist2 were detected at very low levels and not significantly regulated as well. These data suggest that, at the chosen experimental conditions, while a clear adaptive phenotypic cell plasticity is observed, classical EMT-like programs are not prominently activated. However, we cannot exclude the possibility that longer culture durations or additional cues could induce such transitions.

      • Lines 235-236, the authors write that ECM proteins regulate melanocyte behaviour "likely through modulation of MITF localization and activity". Could the authors support the role of MITF experimentally? Genetic experiments using different MITF mutants could address this question.

      To experimentally support the role of MITF, we now performed melanin assays following siRNA-mediated knockdown of MITF in MCs grown on COL I or FN. On COL I-coated substrates, MITF depletion led to a marked reduction in melanin content, supporting the conclusion that ECM-dependent regulation of pigmentation in our culture model involves MITF activity. These findings are now included in the revised manuscript (lines 244-245, revised fig. 4D, new fig. S4B).

      • *Additionally, how does MEK/ERK signalling control MITF activity in these melanocytes? The trametinib experiment should be consolidated with other inhibitors (including ERK inhibitors) and/or genetic manipulation. *

      To address this comment, we complemented our former Trametinib experiments with ERK inhibition using Ravoxertinib (new fig. 6J-L). ERK inhibition led to increased nuclear localization of MITF and elevated melanin production, supporting the involvement of MEK/ERK in restraining MITF activity in MCs in response to ECM molecules. These new data are now included in the revised manuscript (line 354 ff. and new fig. 6J-L).

      • Did the authors also measure the effect of trametinib on cell proliferation in Figure 5?

      Overall, compared to the observed pronounced phenotypes like ECM-dependent cell morphology, melanin production and others, the differences in cell proliferation of MCs grown at different ECM conditions were statistically significant but not very large. We therefore refrained from additionally assessing the effect of trametinib on the observed ECM-dependent MC behaviour. Given the well-established role of ERK signaling in promoting cell proliferation, we indeed expect that MEK inhibition can reduce MC proliferation in our system, though it remains open whether there is an ECM-specific aspect to this.

      • Parallels with physiological conditions:*
      • *Most experiments shown were performed with immortalized melanocytes even though authors mention the use of primary cells (pMCs, line 148). Were similar results obtained in primary melanocytes? Do human melanocytes in culture behave similarly? *

      While we have not assessed human MCs, original fig. S2 (__revised fig. S3) __provides data using primary murine MCs (freshly isolated from newborn mice), confirming a similar behavior of primary cells compared to immortalized MCs in terms of cell area, p-FAK levels, number of FAs, melanin production, and MITF nuclear localization.

      • Are some of these observations also true in vivo, for example in mouse skin (optional)?

      The current manuscript focuses on the behavior of MCs in culture, as it was important to use a reductionist model system that can uncouple the effect of distinct ECM types as well as substrate stiffness. However, as a perspective and beyond the scope of this manuscript, we indeed plan to translate our in vitro findings to mouse skin, taking different biophysical and biochemical cues into account. Data from the present in vitro study provides valuable insights into which parameters and which anatomical areas to study in vivo.

      • How do the authors reconciliate their findings that collagen IV induced melanocyte migration and decreased proliferation and melanin production with the fact that melanocytes in human skin are generally in contact with the collagen IV-rich basement membrane?

      We indeed regarded the use of collagen IV (COL IV) as a physiological reference condition, and considered MC migration, proliferation, and melanin production on COL as baseline levels. Relative to COL IV, COL I reduced migration and increased melanin production, while FN led to increased migration, and a decrease of proliferation and melanin production. This suggests that ECM composition can selectively modulate distinct aspects of MC behavior compared to attachment to COL IV. The intermediate state observed on COL IV would be in line with a model in which this abundant basement membrane molecule enables MCs to maintain high flexibility in their phenotype, e.g. to further increase melanin production upon external stimuli other than ECM (UV, inflammation etc.). The perhaps unexpected, opposing response of MCs to FN and COL I, respectively, opens the possibility that under specific (patho)physiological conditions, the then abundant ECM can direct MC behaviour. Both plasma- and cellular-derived FN is deposited upon skin injury and instructs various cell types to promote skin repair. Taking our observations in vitro into account, it is tempting to speculate that this FN-enriched tissue enables MCs to quickly migrate into wound sites to re-establish protection to UV. Conversely, increased COL I levels-as observed in fibrotic conditions such as scleroderma-might favor a more differentiated, pigment-producing phenotype. Interestingly, cases of localized hyperpigmentation have been reported in scleroderma patients, possibly reflecting such matrix-driven MC reprogramming. Though requiring further investigation, these observations open new avenues to explore how dynamic changes in ECM composition contribute to MC behavior in tissue homeostasis and repair.

      We now extended our original discussion to better emphasize the physiological relevance of our findings (lines 383-391) and hypothesize how ECM remodeling may contribute to the dynamic regulation of MC plasticity-not only during tissue homeostasis, but also in response to injury and in fibrotic conditions such as scleroderma (lines 393-406).

      Minor comments to the Authors:

      The evidence that FAK is not responsible for MEK/ERK activation could be presented in the main text rather than in the discussion.

      We thank the reviewer for highlighting this important point. Our initial conclusion-that ERK activation was independent of FAK-likely stemmed from limitations of the previously used FAK inhibitor (Defactinib). In those earlier experiments, while FAK inhibition reduced focal adhesion numbers, p-FAK levels were not properly decreased, and paradoxically, ERK phosphorylation increased alongside decreased nuclear MITF levels. Based on this initial discrepancy and because of this reviewer's comment, we performed additional experiments using another selective FAK inhibitor, Ifebemtinib, which achieved an effective reduction in both p-FAK levels and focal adhesion number (new suppl. fig. S6B, C). In the revised version, we present new experiments using Ifebemtinib, demonstrating that FAK inhibition in fact does reduce p-ERK levels (new fig. 6M-N), thus supporting the notion that FAK contributes to ECM-dependent ERK pathway activation in our model. These findings are now shown in the results section (lines 357-364).

      Significance:

      General assessment: This study establishes the cellular impact of different types of extracellular matrix proteins and stiffness conditions relevant to skin biology on the behaviour of untransformed mouse melanocytes. In particular, it shows opposite effects of fibronectin and collagen I on cell proliferation and migration, which could prove relevant to certain skin conditions in human. However, the scope of these results is limited by the incomplete mechanistic characterization of the observed phenotypes and by the lack of parallels with physiological conditions.

      Advance: The systematic comparison of different microenvironmental conditions on normal melanocyte behaviour is novel and opens perspectives to understand the role of melanocytes in some human skin pathologies.

      Audience: The comparison of different environmental conditions on melanocyte behaviour is of interest to the melanocyte biology community and could have implications for basic and clinical understanding of some skin diseases.

      My expertise is in melanoma biology, including the impact of the microenvironment on tumour cell behaviours.

      1. Reviewer #3 Evidence, reproducibility and clarity:

      In this manuscript Luthold et al. describe how extracelluar matrix proteins and mechanosensation affect melanocyte differentiation. In particular, they show that ECM proteins and surface stiffness lead to effects on the MEK/ERK pathway, thus affecting the MITF transcription factor. The manuscript is interesting, well written and the data presented in a clear and easy-to-follow manner. The data are nicely quantitated and largely convincing.

        • However, the discussion of the nuclear location of MITF (Figure 4A) is not convincing. The images presented show that upon exposure to ColI, there is a lot of MITF in the nucleus, a lot less so upon ColIV and none upon FN exposure. However, we only see a snapshot of the cells and thus we do not know if we are witnessing effects on MITF protein synthesis, degradation or nuclear localization (the least likely scenario since M-MITF, the isoform present in melanocytes is predominantly nuclear anyway). Was there a cytoplasmic signal detected? Upon FN treatment, there is no MITF protein visible in the cells. Does this mean that the protein is not made, that it is degraded or present at such low levels that the antibody does not detect it? The claim of the authors that this affects nuclear localization of MITF needs more corroboration. *

      We thank the reviewer for raising this important point regarding the interpretation of MITF localization. We agree that the data as represented in the original figure 4 cannot distinguish whether changes reflect differences in MITF expression, stability, or subcellular distribution.

      To better address this, we now included a quantitative analysis of both nuclear and cytoplasmic MITF signals (revised fig. 4B). These data show that MITF is detectable in both compartments at all conditions tested. While total MITF levels were not reduced on FN, nuclear MITF was markedly decreased and cytoplasmic MITF was even increased compared to COL I. This indicates that the reduced nuclear signal on FN compared to COL I is not due to an overall loss of MITF protein but rather reflects a shift in its subcellular distribution. These findings support the idea that ECM composition influences MITF localization, consistent with functional changes in its activity and with the observed phenotypic changes.

      • Also, the authors need to show immunocytochemical images for the effects on MITF nuclear localization for the images presented in Figure 5C. *

      As requested, we now provide representative micrographs illustrating the effects on MITF nuclear localization corresponding to the conditions shown in Fig. 5C. These images have been included in the revised version of the manuscript (new fig. 6G), further supporting the quantitative data presented.

      • It seems that the authors quantitated immune-reactivity for both MITF and YAP. What was the control and how was the data normalized? *

      MITF and YAP immunodetection were performed in separate experiments and were not analyzed in the same cells. For both stainings, secondary antibody controls were included (secondary antibody alone without primary antibody), which showed no detectable signal. For MITF and YAP quantifications (revised fig. 4B,F), nuclear (for both) and cytoplasmic (for MITF) intensity values were normalized within each independent experiment by dividing each individual measurement by the mean nuclear intensity across all conditions. This approach allowed us to deal with total signal variability between experiments while preserving relative differences between ECM conditions. For the percentage of nuclear MITF no normalization was applied. We have added this description to the revised methods section.

      • Similarly, the blots and data shown in Figure 5 are not consistent with the text as described in the results section. The differences observed are minor and the only set that is likely to be significant is the FN-set; the differences between soft, intermediate and stiff of the FN-set do not look significantly different. The description of this in the results section should be toned down accordingly.*

      To strengthen the conclusions drawn from the original Fig. 5 (now fig. 6), we performed additional immunoblot experiments to increase the number of replicates. These extended results now show a statistically significant increase in pERK levels in MCs cultured on FN compared to COL I. However, consistent with the reviewer's observation, no significant differences were detected across the stiffness conditions within FN. We have revised the Results section accordingly to tone down the interpretation and to better reflect the revised data (revised fig. 6E, lines 339-355).

      Significance:

      Upon improvement, this paper will provide an early characterization of the effects of the ECM on melanocyte differentiation. If the link to MITF holds, this will be the first time that mechanosensation has been shown to mediate effects on this transcription factor.

    2. 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

      Summary:

      In this manuscript, authors demonstrated the role of ECM-dependent MEK/ERK/MITF signaling pathway that influences the plasticity of MCs (melanocytes) through their interactions with the environment. The findings emphasize the essential role of the extracellular matrix (ECM) in controlling MC function and differentiation, highlighting a critical need for further research to understand the complex interactions between mechanical factors and ECM components in the cellular microenvironment. Overall, the manuscript is concise, written well and shed light on a complex relationship between ECM protein types and substrate stiffness that affects MC mechanosensation. However, understanding detailed molecular mechanisms involved, especially the roles of MITF and other key regulators, is crucial for comprehending MC function and related pathologies. Authors needs to clarify some minor queries to be considered for publication.

      Major comment:

      1. Authors have chosen ERK signaling pathways to test and draw their conclusion based on existing knowledge in the field, as several studies previously reported the role of ECM to modulate the ERK signaling pathway but it would be interesting to test other signaling pathways unbiasedly; e.g. ECM can also regulate Wnt signaling (PMID: 29454361) and connection of MITF and its target gene TYR expression is also regulated by Wnt in context of melanocyte. (PMID: 29454361, PMID: 34878101, PMID: 38020918).
      2. Discussion line 340-344. Please provide the data as it is directly connected to the study, and it would be crucial to interpret data better. As FAK is upregulated and FAK inhibitor did not reduce pERK, is there any possibility that other kinases might involve. Please discuss. Again, authors should check Wnt activation as FAK can activate Wnt signaling in response to matrix stiffness as well. (PMID 29454361).
      3. Rationale for selecting MITF for the study is very weak. Please justify in the discussion why authors have chosen to study MITF/ERK axis with a more logistic approach.
      4. It is suggested to check for the changes in the transcriptomic profile of melanocytes upon culturing on different matrix to get a more comprehensive view associated with the molecular mechanisms involved.
      5. Please provide the protein expression of genes involved in cell cycle progression and/or apoptosis to support the data in Fig. 3D-E.

      Minor comment:

      1. Discussion line 358-359, using term synergy is an overstatement as the collective data do not support the claim. Very little role of matrix stiffness is demonstrated by experimental data.
      2. Method section, BrdU assay and BrdU assay-cell proliferation can be combined in method section.
      3. What trigger melanocytes to respond to different microenvironment. Please discuss.
      4. Fig 3C and 5D Tyr mRNA expression is tested. Authors should also test for the protein expression in the similar set of studies.
      5. Line 217-218, Authors claim stiffness mediated increase of MITF nuclear localization in Col I, however Fig. 4A-B does not represent that claim. Please justify.

      Significance

      Overall, the study is well-planned, the experiments are well-designed and executed with appropriate use of statistical analysis. However, a more in-depth analysis of the molecular mechanisms is necessary to clarify how the extracellular matrix (ECM) regulates ERK or MITF nuclear translocation.

      This study enhances our existing knowledge by linking the well-established role of the extracellular matrix (ECM) in regulating ERK signaling to ERK's involvement in controlling MITF, a key regulator of melanocyte differentiation. It further establishes the ECM's role in controlling melanocyte function and differentiation.

      This study will interest readers working in the field of the tumor microenvironment, as it explores the role of the extracellular matrix and its complexity and stiffness in disease progression, not only in melanoma but also in other types of cancer.

    1. Author response:

      The following is the authors’ response to the original reviews

      Reviewer 1 (Public review):

      Summary:

      Gene transfer agent (GTA) from Bartonella is a fascinating chimeric GTA that evolved from the domestication of two phages. Not much is known about how the expression of the BaGTA is regulated. In this manuscript, Korotaev et al noted the structural similarity between BrrG (a protein encoded by the ror locus of BaGTA) to a well-known transcriptional anti-termination factor, 21Q, from phage P21. This sparked the investigation into the possibility that BaGTA cluster is also regulated by anti-termination. Using a suite of cell biology, genetics, and genome-wide techniques (ChIP-seq), Korotaev et al convincingly showed that this is most likely the case. The findings offer the first insight into the regulation of GTA cluster (and GTA-mediated gene transfer) particularly in this pathogen Bartonella. Note that anti-termination is a well-known/studied mechanism of transcriptional control. Anti-termination is a very common mechanism for gene expression control of prophages, phages, bacterial gene clusters, and other GTAs, so in this sense, the impact of the findings in this study here is limited to Bartonella.

      Strengths:

      Convincing results that overall support the main claim of the manuscript.

      Weaknesses:

      A few important controls are missing.

      We sincerely appreciate reviewer #1's positive assessment of our manuscript. In response to the concern regarding control samples/experiments, we have addressed this issue in our revision, by providing data of the replicates of our experiments. We acknowledge that antitermination is a well-established mechanism of expression control in bacteria, including bacterial gene clusters, phages, prophages, and at least one other GTA. As reviewer #2 also noted, our study presents a unique example of phage co-domestication, where antitermination integrates both phage remnants at the regulatory level. We have emphasized this original aspect more clearly in the revised manuscript.

      Reviewer 1 (Recommendations for the authors):

      (1) Provide Rsmd and DALI scores to show how similar the AlphaFold-predicted structures of BrrG are to other anti-termination factors. This should be done for Fig1B and also for Suppl. Fig 1 to support the claim that BrrG, GafA, GafZ, Q21 share structural features.

      In the revised manuscript we provide Rsmd and DALI scores in the supplementary Fig. 1A (Suppl. Fig. 1A). In Suppl. Fig. 1B we further include a heatmap of similiarity values.

      (2) Throughout the manuscript, flow cytometry data of gfp expression was used and shown as single replicate. Korotaev et al wrote in the legends that error bars are shown (that is not true for e.g. Figs. 3, 4, and 5). It is difficult for reviewers/readers to gauge how reliable are their experiments.

      In the revised manuscript we show all replicates for the flow cytometry histograms.

      For Fig. 2C, all replicates are provided in Suppl. Fig. 3.

      For Fig. 3B, all replicates are provided in Suppl. Fig. 4.

      For Fig. 4B, all replicates are provided in Suppl. Fig. 5.

      For Fig. 5B, all replicates are provided in Suppl. Fig. 6.

      (3) I am unsure how ChIP-seq in Fig. 2A was performed (with anti-FLAG or anti-HA antibodies? I cannot tell from the Materials & Methods). More importantly, I did not see the control for this ChIP-seq experiment. If a FLAG-tagged BrrG was used for ChIP-seq, then a WT non-tagged version should be used as a negative control (not sequencing INPUT DNA), this is especially important for anti-terminator that can co-travel with RNA polymerase. Please also report the number of replicates for ChIP-seq experiments.

      Fig. 2A presents the coverage plot from the ChIP-Seq of ∆brrG +pPtet:3xFLAG-brrG (N’ in green). As anticipated by the referee, we had used ∆brrG +pTet:brrG (untagged) as control (grey). Each strain was tested in a single replicate. The C-terminal tag produced results similar to the untagged version, suggesting it is non-functional. All tested tags are shown in Supplementary Figure 2.

      (4) Korotaev et al mentioned that BrrG binds to DNA (as well as to RNA polymerase). With the availability of existing ChIP-seq data, the authors should be able to locate the DNA-binding element of BrrG, this additional information will be useful to the community.

      We identified a putative binding site of BrrG using our ChIP-Seq data. The putative binding site is indicated in Fig. 2D of the revised manuscript.

      (5) Mutational experiments to break the potential hairpin structure are required to strengthen the claim that this putative hairpin is the potential transcriptional terminator.

      We did not claim the identified hairpin is a confirmed terminator, but proposed it as a candidate. We agree with the referee that the suggested experiment would be necessary to definitively establish its function. However, our main objective was to show that BrrG acts as a processive terminator, which we demonstrated by replacing the putative terminator with a well-characterized synthetic one that BrrG successfully bypassed. Therefore, we chose not to perform the proposed experiment and have accordingly softened our conclusions regarding the hairpin’s potential terminator function.

      Reviewer 2 (Public review):

      Summary:

      In this study, the authors identified and characterized a regulatory mechanism based on transcriptional anti-termination that connects the two gene clusters, capsid and run-off replication (ROR) locus, of the bipartite Bartonella gene transfer agent (GTA). Among genes essential for GTA functionality identified in a previous transposon sequencing project, they found a potential antiterminatior of phage origin within the ROR locus. They employed fluorescence reporter and gene transfer assays of overexpression and knockout strains in combination with ChiPSeq and promoter-fusions to convincingly show that this protein indeed acts as an antiterminator counteracting attenuation of the capsid gene cluster expression.

      Impact on the field:

      The results provide valuable insights into the evolution of the chimeric BaGTA, a unique example of phage co-domestication by bacteria. A similar system found in the other broadly studied Rhodobacterales/Caulobacterales GTA family suggests that antitermination could be a general mechanism for GTA control.

      Strengths:

      Results of the selected and carefully designed experiments support the main conclusions.

      Weaknesses:

      It remains open why overexpression of the antiterminator does not increase the gene transfer frequency.

      We are grateful for reviewer #2's thoughtful and encouraging feedback on our manuscript. The reviewer raises an important question about why overexpression of the antiterminator does not increase gene transfer frequency. While we acknowledge this point, we consider it beyond the scope of the current study. Our findings clearly demonstrate that the antiterminator induces capsid component expression in a large proportion of cells. However, the fact that this expression plateaus at high levels rather than exhibiting a transient peak, as seen in the wild type, suggests that antiterminators do not regulate GTA particle release via lysis. We are actively investigating this further through additional experiments, which we plan to publish separately from this study.

      Reviewer 2 (Recommendations for the authors):

      (1) The authors wrote "GTAs are not self-transmitting because the DNA packaging capacity of a GTA particle is too small to package the entire gene cluster encoding it" (page 3). I thought that at least the Bartonella capsid gene cluster should be self-transmissible within the 14 kb packaged DNA (https://doi.org/10.1371/journal.pgen.1003393, https://doi.org/10.1371/journal.pgen.1000546). This was also concluded by Lang et al (https://doi.org/10.1146/annurev-virology-101416-041624). In this case the presented results would have important implications. As the gene cluster and the anti-terminator required for its expression are separated on the chromosome, it would not be possible to transfer an active GTA gene cluster, although the DNA coding for the genes required for making the packaging agent itself, theoretically fits into a BaGTA particle. Could the authors comment on that? I think it would be helpful to add the sizes of the different gene clusters and the distance between them in Fig. 2A. The ROR amplified region spans 500kb, is the capsid gene cluster within this region?

      We thank the reviewer for bringing up this interesting point. The ror gene cluster, which encodes the antiterminator BrrG, is approximately 9.2 kb in size and could feasibly be packaged in its entirety into a GTA particle. In contrast, the bgt cluster (capsid cluster) is approximately 20 kb in size —exceeding the packaging limit of GTA particles—and is separated from the bgt cluster by approximately 35 kb. Consequently, if the ror cluster is transferred via a GTA particle into a recipient host that does not encode the bgt gene cluster, the ror cluster would not be expressed.

      We added the sizes of the gene clusters to Fig. 1A.

      (2) Another side-note regarding the introduction: On page three the authors write: "GTAs encode bacteriophage-like particles and in contrast to phages transfer random pieces of host bacterial DNA". While packaging is not specific, certain biases in the packaging frequency are observed in both studied GTA families. For Bartonella this is ROR. In the two GTA-producing strains D. shibae and C. crescentus origin and terminus of replication are not packaged and certain regions are overrepresented (https://doi.org/10.1093/gbe/evy005, https://doi.org/10.1371/journal.pbio.3001790). Furthermore, D. shibae plasmids are not packaged but chromids are. I think the term "random" does not properly describe these observations. I would suggest using "not specific" instead.

      We thank the reviewer for this suggestion and adjusted the wording on p. 3 accordingly.

      (3) Page 5: Remove "To address this". It is not needed as you already state "To test this hypothesis" in the previous sentence.

      We adjusted the working on p.5 accordingly.

      (4) I think the manuscript would greatly benefit from a summary figure to visualize the Q-like antiterminator-dependent regulatory circuit for GTA control and its four components described on pages 15 and 16.

      We thank the reviewer for this valuable suggestion. We included a summary figure (Fig. 6) in the discussion section of the revised manuscript.

      (5) Page 17: It might be worth noting that GafA is highly conserved along GTAs in Rhodobacterales (https://doi.org/10.3389/fmicb.2021.662907) and so is probably regulatory integration into the ctrA network (https://doi.org/10.3389/fmicb.2019.00803). It's an old mechanism. It would be also interesting to know if it is a common feature of the two archetypical GTAs that the regulator is not part of the cluster itself.

      We agree with the reviewer’s comments and have revised the wording to state that GafA is highly conserved.

    1. Author response:

      The following is the authors’ response to the previous reviews

      General Response to Reviewers:

      We thank the Reviewers for their comments, which continue to substantially improve the quality and clarity of the manuscript, and therefore help us to strengthen its message while acknowledging alternative explanations.

      All three reviewers raised the concern that we have not proven that Rab3A is acting on a presynaptic mechanism to increase mEPSC amplitude after TTX treatment of mouse cortical cultures.  The reviewers’ main point is that we have not shown a lack of upregulation of postsynaptic receptors in mouse cortical cultures. We want to stress that we agree that postsynaptic receptors are upregulated after activity block in neuronal cultures.  However, the reviewers are not acknowledging that we have previously presented strong evidence at the mammalian NMJ that there is no increase in AChR after activity blockade, and therefore the requirement for Rab3A in the homeostatic increase in quantal amplitude points to a presynaptic contribution. We agree that we should restrict our firmest conclusions to the data in the current study, but in the Discussion we are proposing interpretations. We have added the following new text:

      “The impetus for our current study was two previous studies in which we examined homeostatic regulation of quantal amplitude at the NMJ.  An advantage of studying the NMJ is that synaptic ACh receptors are easily identified with fluorescently labeled alpha-bungarotoxin, which allows for very accurate quantification of postsynaptic receptor density. We were able to detect a known change due to mixing 2 colors of alpha-BTX to within 1% (Wang et al., 2005).  Using this model synapse, we showed that there was no increase in synaptic AChRs after TTX treatment, whereas miniature endplate current increased 35% (Wang et al., 2005). We further showed that the presynaptic protein Rab3A was necessary for full upregulation of mEPC amplitude (Wang et al., 2011). These data strongly suggested Rab3A contributed to homeostatic upregulation of quantal amplitude via a presynaptic mechanism.  With the current study showing that Rab3A is required for the homeostatic increase in mEPSC amplitude in cortical cultures, one interpretation is that in both situations, Rab3A is required for an increase in the presynaptic quantum.”

      The point we are making is that the current manuscript is an extension of that work and interpretation of our findings regarding the variability of upregulation of postsynaptic receptors in our mouse cortical cultures further supports the idea that there is a Rab3Adependent presynaptic contribution to homeostatic increases in quantal amplitude.

      Public Reviews:

      Reviewer #1 (Public review):

      Koesters and colleagues investigated the role of the small GTPase Rab3A in homeostatic scaling of miniature synaptic transmission in primary mouse cortical cultures using electrophysiology and immunohistochemistry. The major finding is that TTX incubation for 48 hours does not induce an increase in the amplitude of excitatory synaptic miniature events in neuronal cortical cultures derived from Rab3A KO and Rab3A Earlybird mutant mice. NASPM application had comparable effects on mEPSC amplitude in control and after TTX, implying that Ca2+-permeable glutamate receptors are unlikely modulated during synaptic scaling. Immunohistochemical analysis revealed no significant changes in GluA2 puncta size, intensity, and integral after TTX treatment in control and Rab3A KO cultures. Finally, they provide evidence that loss of Rab3A in neurons, but not astrocytes, blocks homeostatic scaling. Based on these data, the authors propose a model in which neuronal Rab3A is required for homeostatic scaling of synaptic transmission, potentially through GluA2-independent mechanisms.

      The major finding - impaired homeostatic up-scaling after TTX treatment in Rab3A KO and Rab3 earlybird mutant neurons - is supported by data of high quality. However, the paper falls short of providing any evidence or direction regarding potential mechanisms. The data on GluA2 modulation after TTX incubation are likely statistically underpowered, and do not allow drawing solid conclusions, such as GluA2-independent mechanisms of up-scaling.

      The study should be of interest to the field because it implicates a presynaptic molecule in homeostatic scaling, which is generally thought to involve postsynaptic neurotransmitter receptor modulation. However, it remains unclear how Rab3A participates in homeostatic plasticity.

      Major (remaining) point:

      (1) Direct quantitative comparison between electrophysiology and GluA2 imaging data is complicated by many factors, such as different signal-to-noise ratios. Hence, comparing the variability of the increase in mini amplitude vs. GluA2 fluorescence area is not valid. Thus, I recommend removing the sentence "We found that the increase in postsynaptic AMPAR levels was more variable than that of mEPSC amplitudes, suggesting other factors may contribute to the homeostatic increase in synaptic strength." from the abstract.

      We have not removed the statement, but altered it to soften the conclusion. It now reads, “We found that the increase in postsynaptic AMPAR levels in wild type cultures was more variable than that of mEPSC amplitudes, which might be explained by a presynaptic contribution, but we cannot rule out variability in the measurement.”.

      Similarly, the data do not directly support the conclusion of GluA2-independent mechanisms of homeostatic scaling. Statements like "We conclude that these data support the idea that there is another contributor to the TTX- induced increase in quantal size." should be thus revised or removed.

      This particular statement is in the previous response to reviewers only, we deleted the sentence that starts, “The simplest explanation Rab3A regulates a presynaptic contributor….”. and “Imaging of immunofluorescence more variable…”. We deleted “ our data suggest….consistently leads to an increase in mEPSC amplitude and sometimes leads to….” We added “…the lack of a robust increase in receptor levels leaves open the possibility that there is a presynaptic contributor to quantal size in mouse cortical cultures. However, the variability could arise from technical factors associated with the immunofluorescence method, and the mechanism of Rab3A-dependent plasticity could be presynaptic for the NMJ and postsynaptic for cortical neurons.”

      Reviewer #2 (Public review):

      I thank the authors for their efforts in the revision. In general, I believe the main conclusion that Rab3A is required for TTX-induced homeostatic synaptic plasticity is wellsupported by the data presented, and this is an important addition to the repertoire of molecular players involved in homeostatic compensations. I also acknowledge that the authors are more cautious in making conclusions based on the current evidence, and the structure and logic have been much improved.

      The only major concern I have still falls on the interpretation of the mismatch between GluA2 cluster size and mEPSC amplitude. The authors argue that they are only trying to say that changes in the cluster size are more variable than those in the mEPSC amplitude, and they provide multiple explanations for this mismatch. It seems incongruous to state that the simplest explanation is a presynaptic factor when you have all these alternative factors that very likely have contributed to the results. Further, the authors speculate in the discussion that Rab3A does not regulate postsynaptic GluA2 but instead regulates a presynaptic contributor. Do the authors mean that, in their model, the mEPSC amplitude increases can be attributed to two factors- postsynaptic GluA2 regulation and a presynaptic contribution (which is regulated by Rab3A)? If so, and Rab3A does not affect GluA2 whatsoever, shouldn't we see GluA2 increase even in the absence of Rab3A? The data in Table 1 seems to indicate otherwise.

      The main body of this comment is addressed in the General Response to Reviewers. In addition, we deleted text “current data, coupled with our previous findings at the mouse neuromuscular junction, support the idea that there are additional sources contributing to the homeostatic increase in quantal size.” We added new text, so the sentence now reads: “Increased receptors likely contribute to increases in mESPC amplitudes in mouse cortical cultures, but because we do not have a significant increase in GluA2 receptors in our experiments, it is impossible to conclude that the increase is lacking in cultures from Rab3A<sup>-/-</sup> neurons.”

      I also question the way the data are presented in Figure 5. The authors first compare 3 cultures and then 5 cultures altogether, if these experiments are all aimed to answer the same research question, then they should be pooled together. Interestingly, the additional two cultures both show increases in GluA2 clusters, which makes the decrease in culture #3 even more perplexing, for which the authors comment in line 261 that this is due to other factors. Shouldn't this be an indicator that something unusual has happened in this culture?

      Data in this figure is sufficient to support that GluA2 increases are variable across cultures, which hardly adds anything new to the paper or to the field. 

      A major goal of performing the immunofluorescence measurements in the same cultures for which we had electrophysiological results was to address the common impression that the homeostatic effect itself is highly variable, as the reviewer notes in the comment “…GluA2 increases are variable across cultures…” Presumably, if GluA2 increases are the mechanism of the mEPSC amplitude increases, then variable GluA2 increases should correlate with variable mEPSC amplitude increases, but that is not what we observed. We are left with the explanation that the immunofluorescence method itself is very variable. We have added the point to the Discussion, which reads, “the variability could arise from technical factors associated with the immunofluorescence method, and the mechanism of Rab3A-dependent homeostatic plasticity could be presynaptic for the NMJ and postsynaptic for cortical neurons.”

      Finally, the implication of “Shouldn’t this be an indicator that something unusual has happened in this culture?” if it is not due to culture to culture variability in the homeostatic response itself, is that there was a technical problem with accurately measuring receptor levels. We have no reason to suspect anything was amiss in this set of coverslips (the values for controls and for TTX-treated were not outside the range of values in other experiments). In any of the coverslips, there may be variability in the amount of primary anti-GluA2 antibody, as this was added directly to the culture rather than prepared as a diluted solution and added to all the coverslips. But to remove this one experiment because it did not give the expected result is to allow bias to direct our data selection.

      The authors further cite a study with comparable sample sizes, which shows a similar mismatch based on p values (Xu and Pozzo-Miller 2007), yet the effect sizes in this study actually match quite well (both ~160%). P values cannot be used to show whether two effects match, but effect sizes can. Therefore, the statement in lines 411-413 "... consistently leads to an increase in mEPSC amplitudes, and sometimes leads to an increase in synaptic GluA2 receptor cluster size" is not very convincing, and can hardly be used to support "the idea that there are additional sources contributing to the homeostatic increase in quantal size.”

      We have the same situation; our effect sizes match (19.7% increase for mEPSC amplitude; 18.1% increase for GluA2 receptor cluster size, see Table 1), but in our case, the p value for receptors does not reach statistical significance. Our point here is that there is published evidence that the variability in receptor measurements is greater than the variability in electrophysiological measurements. But we have softened this point, removing the sentences containing “…consistently leads and sometimes...” and “……additional sources contributing…”.

      I would suggest simply showing mEPSC and immunostaining data from all cultures in this experiment as additional evidence for homeostatic synaptic plasticity in WT cultures, and leave out the argument for "mismatch". The presynaptic location of Rab3A is sufficient to speculate a presynaptic regulation of this form of homeostatic compensation.

      We have removed all uses of the word “mismatch,” but feel the presentation of the 3 matched experiments, 23-24 cells (Figure 5A, D), and the additional 2 experiments for a total of 5 cultures, 48-49 cells (Figure 5C, F), is important in order to demonstrate that the lack of statistically significant receptor response is due neither to a variable homeostatic response in the mEPSC amplitudes, nor to a small number of cultures.

      Minor concerns:

      (1) Line 214, I see the authors cite literature to argue that GluA2 can form homomers and can conduct currents. While GluA2 subunits edited at the Q/R site (they are in nature) can form homomers with very low efficiency in exogenous systems such as HEK293 cells (as done in the cited studies), it's unlikely for this to happen in neurons (they can hardly traffic to synapses if possible at all).

      We were unable to identify a key reference that characterized GluA2 homomers vs. heteromers in native cortical neurons, but we have rewritten the section in the manuscript to acknowledge the low conductance of homomers:

      “…to assess whether GluA2 receptor expression, which will identify GluA2 homomers and GluA2 heteromers (the former unlikely to contribute to mEPSCs given their low conductance relative to heteromers (Swanson et al., 1997; Mansour et al., 2001)…”

      (2) Lines 221-222, the authors may have misinterpreted the results in Turrigiano 1998. This study does not show that the increase in receptors is most dramatic in the apical dendrite, in fact, this is the only region they have tested. The results in Figures 3b-c show that the effect size is independent of the distance from soma.

      Figure 3 in Turrigiano et al., shows that the increase in glutamate responsiveness is higher at the cell body than along the primary dendrite. We have revised our description to indicate that an increase in responsiveness on the primary dendrite has been demonstrated in Turrigiano et al. 1998.

      “We focused on the primary dendrite of pyramidal neurons as a way to reduce variability that might arise from being at widely ranging distances from the cell body, or, from inadvertently sampling dendritic regions arising from inhibitory neurons. In addition, it has been shown that there is a clear increase in response to glutamate in this region (Turrigiano et al., 1998).”

      “…synaptic receptors on the primary dendrite, where a clear increase in sensitivity to exogenously applied glutamate was demonstrated (see Figure 3 in (Turrigiano et al., 1998)).

      (3) Lines 309-310 (and other places mentioning TNFa), the addition of TNFa to this experiment seems out of place. The authors have not performed any experiment to validate the presence/absence of TNFa in their system (citing only 1 study from another lab is insufficient). Although it's convincing that glia Rab3A is not required for homeostatic plasticity here, the data does not suggest Rab3A's role (or the lack of) for TNFa in this process.

      We have modified the paragraph in the Discussion that addresses the glial results, to describe more clearly the data that supported an astrocytic TNF-alpha mechanism: “TNF-alpha accumulates after activity blockade, and directly applied to neuronal cultures, can cause an increase in GluA1 receptors, providing a potential mechanism by which activity blockade leads to the homeostatic upregulation of postsynaptic receptors (Beattie et al., 2002; Stellwagen et al., 2005; Stellwagen and Malenka, 2006).”

      We have also acknowledged that we cannot rule out TNF-alpha coming from neurons in the cortical cultures: “…suggesting the possibility that neuronal Rab3A can act via a non-TNF-alpha mechanism to contribute to homeostatic regulation of quantal amplitude, although we have not ruled out a neuronal Rab3A-mediated TNF-alpha pathway in cortical cultures.”

      Reviewer #3 (Public review):

      This manuscript presents a number of interesting findings that have the potential to increase our understanding of the mechanism underlying homeostatic synaptic plasticity (HSP). The data broadly support that Rab3A plays a role in HSP, although the site and mechanism of action remain uncertain.

      The authors clearly demonstrate that Rab3A plays a role in HSP at excitatory synapses, with substantially less plasticity occurring in the Rab3A KO neurons. There is also no apparent HSP in the Earlybird Rab3A mutation, although baseline synaptic strength is already elevated. In this context, it is unclear if the plasticity is absent, already induced by this mutation, or just occluded by a ceiling effect due to the synapses already being strengthened. Occlusion may also occur in the mixed cultures when Rab3A is missing from neurons but not astrocytes. The authors do appropriately discuss these options. The authors have solid data showing that Rab3A is unlikely to be active in astrocytes, Finally, they attempt to study the linkage between changes in synaptic strength and AMPA receptor trafficking during HSP, and conclude that trafficking may not be solely responsible for the changes in synaptic strength during HSP.

      Strengths:

      This work adds another player into the mechanisms underlying an important form of synaptic plasticity. The plasticity is likely only reduced, suggesting Rab3A is only partially required and perhaps multiple mechanisms contribute. The authors speculate about some possible novel mechanisms, including whether Rab3A is active pre-synaptically to regulate quantal amplitude.

      As Rab3A is primarily known as a pre-synaptic molecule, this possibility is intriguing. However, it is based on the partial dissociation of AMPAR trafficking and synaptic response and lacks strong support. On average, they saw a similar magnitude of change in mEPSC amplitude and GluA2 cluster area and integral, but the GluA2 data was not significant due to higher variability. It is difficult to determine if this is due to biology or methodology - the imaging method involves assessing puncta pairs (GluA2/VGlut1) clearly associated with a MAP2 labeled dendrite. This is a small subset of synapses, with usually less than 20 synapses per neuron analyzed, which would be expected to be more variable than mEPSC recordings averaged across several hundred events. However, when they reduce the mEPSC number of events to similar numbers as the imaging, the mESPC amplitudes are still less variable than the imaging data. The reason for this remains unclear. The pool of sampled synapses is still different between the methods and recent data has shown that synapses have variable responses during HSP. Further, there could be variability in the subunit composition of newly inserted AMPARs, and only assessing GluA2 could mask this (see below). It is intriguing that pre-synaptic changes might contribute to HSP, especially given the likely localization of Rab3A. But it remains difficult to distinguish if the apparent difference in imaging and electrophysiology is a methodological issue rather than a biological one. Stronger data, especially positive data on changes in release, will be necessary to conclude that pre-synaptic factors are required for HSP, beyond the established changes in post-synaptic receptor trafficking.

      Regarding the concern that the lack of increase in receptors is due to a technical issue, please see General Response to Reviewers, above. We have also softened our conclusions throughout, acknowledging we cannot rule out a technical issue.

      Other questions arise from the NASPM experiments, used to justify looking at GluA2 (and not GluA1) in the immunostaining. First, there is a strong frequency effect that is unclear in origin. One would expect NASPM to merely block some fraction of the post-synaptic current, and not affect pre-synaptic release or block whole synapses. But the change in frequency seems to argue (as the authors do) that some synapses only have CP-AMPARs, while the rest of the synapses have few or none. Another possibility is that there are pre-synaptic NASPM-sensitive receptors that influence release probability. Further, the amplitude data show a strong trend towards smaller amplitude following NASPM treatment (Fig 3B). The p value for both control and TTX neurons was 0.08 - it is very difficult to argue that there is no effect. The decrease on average is larger in the TTX neurons, and some cells show a strong effect. It is possible there is some heterogeneity between neurons on whether GluA1/A2 heteromers or GluA1 homomers are added during HSP. This would impact the conclusions about the GluA2 imaging as compared to the mEPSC amplitude data.

      The key finding in Figure 3 is that NASPM did not eliminate the statistically significant increase in mEPSC amplitude after TTX treatment (Fig 3A).  Whether or not NASPM sensitive receptors contribute to mESPC amplitude is a separate question (Fig 3B). We are open to the possibility that NASPM reduces mEPSC amplitude in both control and TTX treated cells (p = 0.08 for both), but that does not change our conclusion that NASPM has no effect on the TTX-induced increase in mEPSC amplitude. The mechanism underlying the decrease in mEPSC frequency following NASPM is interesting, but does not alter our conclusions regarding the role of Rab3A in homeostatic synaptic plasticity of mEPSC amplitude. In addition, the Reviewer does not acknowledge the Supplemental Figure #1, which shows a similar lack of correspondence between homeostatic increases in mEPSC amplitude and GluA1 receptors in two cultures where matched data were obtained. Therefore, we do not think our lack of a robust increase in receptors can be explained by our failing to look at the relevant receptor.

      To understand the role of Rab3A in HSP will require addressing two main issues:

      (1) Is Rab3A acting pre-synaptically, post-synaptically or both? The authors provide good evidence that Rab3A is acting within neurons and not astrocytes. But where it is acting (pre or post) would aid substantially in understanding its role. The general view in the field has been that HSP is regulated post-synaptically via regulation of AMPAR trafficking, and considerable evidence supports this view. More concrete support for the authors' suggestion of a pre-synaptic site of control would be helpful.

      We agree that definitive evidence for a presynaptic role of Rab3A in homeostatic plasticity of mEPSC amplitudes in mouse cortical cultures requires demonstrating that loss of Rab3A in postsynaptic neurons does not disrupt the plasticity, whereas loss in presynaptic neurons does. Without these data, we can only speculate that the Rab3A-dependence of homeostatic plasticity of quantal size in cortical neurons may be similar to that of the neuromuscular junction, where it cannot be receptors. We have added to the Discussion that the mechanism of Rab3A regulation of homeostatic plasticity of quantal amplitude could different between cortical neurons and the neuromuscular junction (lines 448-450 in markup,). Establishing a way to co-culture Rab3A-/- and Rab3A+/+ neurons in ratios that would allow us to record from a Rab3A-/- neuron that has mainly Rab3A+/+ inputs (or vice versa) is not impossible, but requires either transfection or transgenic expression with markers that identify the relevant genotype, and will be the subject of future experiments.

      (2): Rab3A is also found at inhibitory synapses. It would be very informative to know if HSP at inhibitory synapses is similarly affected. This is particularly relevant as at inhibitory synapses, one expects a removal of GABARs or a decrease in GABA release (ie the opposite of whatever is happening at excitatory synapses). If both processes are regulated by Rab3A, this might suggest a role for this protein more upstream in the signaling; an effect only at excitatory synapses would argue for a more specific role just at those synapses.

      We agree with the Reviewer, that it is important to determine the generality of Rab3A function in homeostatic plasticity. Establishing the homeostatic effect on mIPSCs and then examining them in Rab3A-/- cultures is a large undertaking and will be the subject of future experiments.

      Recommendations for the authors:

      Reviewer #1 (Recommendations for the authors):

      Minor (remaining) points:

      (1) The figure referenced in the first response to the reviewers (Figure 5G) does not exist.

      We meant Figure 5F, which has been corrected in the current response.

      (2) I recommend showing the data without binning (despite some overlap).

      The box plot in Origin will not allow not binning, but we can make the bin size so small that for all intents and purposes, there is close to 1 sample in each bin. When we do this, the majority of data are overlapped in a straight vertical line. Previously described concerns were regarding the gaps in the data, but it should be noted that these are cell means and we are not depicting the distributions of mEPSC amplitudes within a recording or across multiple recordings.

      (3) Please auto-scale all axes from 0 (e.g., Fig 1E, F).

      We have rescaled all mEPSC amplitude axes in box plots to go from 0 (Figures 1, 2 and 6).

      (4) Typo in Figure legend 3: "NASPM (20 um)" => uM

      Fixed.

      Reviewer #2 (Recommendations for the authors):

      (1) Line 140, frequencies are reported in Hz while other places are in sec-1, while these are essentially the same, they should be kept consistent in writing.

      All mEPSC frequencies have been changed to sec<sup>-1</sup>, except we have left “Hz” for repetitive stimulation and filtering.

      (2) Paragraph starting from line 163 (as well as other places where multiple groups are compared, such as the occlusion discussion), the authors assessed whether there was a change in baseline between WT and mutant group by doing pairwise tests, this is not the right test. A two-way ANOVA, or at least a multivariant test would be more appropriate.

      We have performed a two-way ANOVA, with genotype as one factor, and treatment as the other factor. The p values in Figures 1 and 2 have been revised to reflect p values from the post-hoc Tukey test on the specific interactions (for each particular genotype, TTX vs CON effects). The difference in the two WT strains, untreated, was not significant in the Post-Hoc Tukey test, and we have revised the text. The difference between the untreated WT from the Rab3A+/Ebd colony and the untreated Rab3AEbd/Ebd mutant was still significant in the Post-Hoc Tukey test, and this has replaced the Kruskal-Wallis test. The two-way ANOVA was also applied to the neuron-glia experiments and p values in Figure 6 adjusted accordingly.

      (3) Relevant to the second point under minor concerns, I suggest this sentence be removed, as reducing variability and avoiding inhibitory projects are reasons good enough to restrict the analysis to the apical dendrites.

      We have revised the description of the Turrigiano et al., 1998 finding from their Figure 3 and feel it still strengthens the justification for choosing to analyze only synapses on the apical dendrite.

      Reviewer #3 (Recommendations for the authors):

      Minor points:

      The comments on lines 256-7 could seem misleading - the NASPM results wouldn't rule out contribution of those other subunits, only non-GluA2 containing combinations of those subunits. I would suggest revising this statement. Also, NASPM does likely have an effect, just not one that changes much with TTX treatment.

      At new line 213 (markup) we have added the modifier “homomeric” to clarify our point that the lack of NASPM effect on the increase in mEPSC amplitude after TTX indicates that the increase is not due to more homomeric Ca<sup>2+</sup>-permeable receptors. We have always stated that NASPM reduces mEPSC amplitude, but it is in both control and treated cultures.

      Strong conclusions based on a single culture (lines 314-5) seem unwarranted.

      We have softened this statement with a “suggesting that” substituted for the previous “Therefore,” but stand by our point that the mEPSC amplitude data support a homeostatic effect of TTX in Culture #3, so the lack of increase in GluA2 cluster size needs an explanation other than variability in the homeostatic effect itself.

      Saying (line 554) something is 'the only remaining possibility' also seems unwarranted.

      We have softened this statement to read, “A remaining possibility…”.

      Beattie EC, Stellwagen D, Morishita W, Bresnahan JC, Ha BK, Von Zastrow M, Beattie MS, Malenka RC (2002) Control of synaptic strength by glial TNFalpha. Science 295:2282-2285.

      Mansour M, Nagarajan N, Nehring RB, Clements JD, Rosenmund C (2001) Heteromeric AMPA receptors assemble with a preferred subunit stoichiometry and spatial arrangement. Neuron 32:841-853. Stellwagen D, Malenka RC (2006) Synaptic scaling mediated by glial TNF-alpha. Nature 440:1054-1059.

      Stellwagen D, Beattie EC, Seo JY, Malenka RC (2005) Differential regulation of AMPA receptor and GABA receptor trafficking by tumor necrosis factor-alpha. J Neurosci 25:3219-3228.

      Swanson GT, Kamboj SK, Cull-Candy SG (1997) Single-channel properties of recombinant AMPA receptors depend on RNA editing, splice variation, and subunit composition. J Neurosci 17:5869.

      Turrigiano GG, Leslie KR, Desai NS, Rutherford LC, Nelson SB (1998) Activity-dependent scaling of quantal amplitude in neocortical neurons. Nature 391:892-896.

      Wang X, Wang Q, Yang S, Bucan M, Rich MM, Engisch KL (2011) Impaired activity-dependent plasticity of quantal amplitude at the neuromuscular junction of Rab3A deletion and Rab3A earlybird mutant mice. J Neurosci 31:3580-3588.

      Wang X, Li Y, Engisch KL, Nakanishi ST, Dodson SE, Miller GW, Cope TC, Pinter MJ, Rich MM (2005) Activity-dependent presynaptic regulation of quantal size at the mammalian neuromuscular junction in vivo. J Neurosci 25:343-351.

    1. 1 - 요구사항 이해. 필요한 사항을 알려주시면 올바른 다음 단계를 파악할 수 있도록 도와드립니다. 2 - 전담 영업 계정 관리자 소개. 자세한 내용을 파악하고, 목표를 이해하고, 솔루션의 범위를 정하기 위해 회의 일정을 잡습니다. 3 - 솔루션 제시. 견적서를 보내드리며, 제안서에 서명하시면 함께 작업을 시작하게 됩니다. 4 - 전담 고객 계획 어드바이저 소개. 고객 계획 어드바이저가 감사인을 배정하고 감사 날짜를 예약해 드립니다. 5 - 감사 제공. 감사인이 1단계 및 2단계 감사를 완료하고 결과를 전달합니다. 6 - 인증서 수령. 결과에 따라 인증서를 발급해 드립니다.

      1. 귀사의 요구 사항 이해. 필요하신 내용을 알려주시면 적절한 다음 단계를 함께 찾아드리겠습니다.

      2. 전담 세일즈 담당자와의 미팅. 전담 세일즈 담당자와의 미팅을 예약하여 귀사의 목표와 요구사항을 자세히 이해하고, 적합한 솔루션을 설계합니다.

      3. 맞춤형 솔루션 제안. 견적서를 보내드리며, 제안서에 서명해주시면 본격적인 협업을 시작합니다.

      4. 전담 고객 지원 담당자 배정. 고객 지원 담당자가 심사원을 배정하고, 심사 일정을 조율합니다.

      5. 심사 수행. 배정된 심사원이 1단계 및 2단계 심사를 진행하고, 결과를 전달 드립니다.

      6. 인증서 발급. 심사 결과를 바탕으로 인증서를 발급해드립니다.

    1. Reviewer #1 (Public review):

      Summary:

      This study uncovers a protective role of the ubiquitin-conjugating enzyme variant Uev1A in mitigating cell death caused by over-expressed oncogenic Ras in polyploid Drosophila nurse cells and by RasK12 in diploid human tumor cell lines. The authors previously showed that overexpression of oncogenic Ras induces death in nurse cells, and now they perform a deficiency screen for modifiers. They identified Uev1A as a suppressor of this Ras-induced cell death. Using genetics and biochemistry, the authors found that Uev1A collaborates with the APC/C E3 ubiquitin ligase complex to promote proteasomal degradation of Cyclin A. This function of Uev1A appears to extend to diploid cells, where its human homologs UBE2V1 and UBE2V2 suppress oncogenic Ras-dependent phenotypes in human colorectal cancer cells in vitro and in xenografts in mice.

      Strengths:

      (1) Most of the data is supported by a sufficient sample size and appropriate statistics.<br /> (2) Good mix of genetics and biochemistry.<br /> (3) Generation of new transgenes and Drosophila alleles that will be beneficial for the community.

      Weaknesses:

      (1) Phenotypes are based on artificial overexpression. It is not clear whether these results are relevant to normal physiology.

      (2) The phenotype of "degenerating ovaries" is very broad, and the study is not focused on phenotypes at the cellular level. Furthermore, no information is provided in the Materials and Methods on how degenerating ovaries are scored, despite this being the most important assay in the study.

      (3) In Figure 5, the authors want to conclude that uev1a is a tumor-suppressor, and so they over-express ubev1/2 in human cancer cell lines that have RasK12 and find reduced proliferation, colony formation, and xenograft size. However, genes that act as tumor suppressors have loss-of-function phenotypes that allow for increased cell division. The Drosophila uev1a mutant is viable and fertile, suggesting that it is not a tumor suppressor in flies. Additionally, they do not deplete human ubev1/2 from human cancer cell lines and assess whether this increases cell division, colony formation, and xenograph growth.

      (4) A critical part of the model does not make sense. CycA is a key part of their model, but they do not show CycA protein expression in WT egg chambers or in their over-expression models (nos.RasV12 or bam>RasV12). Based on Lilly and Spradling 1996, Cyclin A is not expressed in germ cells in region 2-3 of the germarium; whether CycA is expressed in nurse cells in later egg chambers is not shown but is critical to document comprehensively.

      (5) The authors should provide more information about the knowledge base of uev1a and its homologs in the introduction.

    2. Author response:

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      This study uncovers a protective role of the ubiquitin-conjugating enzyme variant Uev1A in mitigating cell death caused by over-expressed oncogenic Ras in polyploid Drosophila nurse cells and by RasK12 in diploid human tumor cell lines. The authors previously showed that overexpression of oncogenic Ras induces death in nurse cells, and now they perform a deficiency screen for modifiers. They identified Uev1A as a suppressor of this Ras-induced cell death. Using genetics and biochemistry, the authors found that Uev1A collaborates with the APC/C E3 ubiquitin ligase complex to promote proteasomal degradation of Cyclin A. This function of Uev1A appears to extend to diploid cells, where its human homologs UBE2V1 and UBE2V2 suppress oncogenic Ras-dependent phenotypes in human colorectal cancer cells in vitro and in xenografts in mice.

      Strengths:

      (1) Most of the data is supported by a sufficient sample size and appropriate statistics.

      (2) Good mix of genetics and biochemistry.

      (3) Generation of new transgenes and Drosophila alleles that will be beneficial for the community.

      We greatly appreciate these comments.

      Weaknesses:

      (1) Phenotypes are based on artificial overexpression. It is not clear whether these results are relevant to normal physiology.

      Downregulation of Uev1A, Ben, and Cdc27 together significantly increased the incidence of dying nurse cells in normal ovaries (Figure 2-figure supplement 4), indicating that the mechanism we uncovered also protects nurse cells from death during normal oogenesis.

      (2) The phenotype of "degenerating ovaries" is very broad, and the study is not focused on phenotypes at the cellular level. Furthermore, no information is provided in the Materials and Methods on how degenerating ovaries are scored, despite this being the most important assay in the study.

      Thanks for pointing out this issue. We quantified the phenotype of nurse cell death using “degrading/total egg chambers per ovary”, not “degenerating ovaries” (see all quantification data in our manuscript). Notably, this phenotype ranges from mild to severe. In normal nurse cells, nuclei exhibit a large, round morphology in DAPI staining (see the first panel in Figure 1D). During early death, nurse cell nuclei become disorganized and begin to condense and fragment (see the third panel in Figure 2-figure supplement 2E). In late-stage death, the nuclei are completely fragmented into small, condensed spherical structures (see the second panel in Figure 1D), making cellular-level phenotypic quantification impossible. Since all nurse cells within the same egg chamber are interconnected, their death process is synchronous. Thus, quantifying the phenotype at the egg-chamber level is more practical than at the cellular level. To improve clarity, we will provide a detailed description of the phenotype and integrate this explanation into the main text of the revised manuscript.

      (3) In Figure 5, the authors want to conclude that uev1a is a tumor-suppressor, and so they over-express ubev1/2 in human cancer cell lines that have RasK12 and find reduced proliferation, colony formation, and xenograft size. However, genes that act as tumor suppressors have loss-of-function phenotypes that allow for increased cell division. The Drosophila uev1a mutant is viable and fertile, suggesting that it is not a tumor suppressor in flies. Additionally, they do not deplete human ubev1/2 from human cancer cell lines and assess whether this increases cell division, colony formation, and xenograph growth.

      We apologize for our misleading description. In Figure 5, we aimed to demonstrate that UBE2V1/2, like Uev1A in Drosophilanos>Ras<sup>G12V</sup>+bam-RNAi” germline tumors (Figure 4), suppress oncogenic KRAS-driven overgrowth in diploid human cancer cells. Importantly, this function of Uev1A and UBE2V1/2 is dependent on Ras-driven tumors; there is no evidence that they act as broad tumor suppressors in the absence of oncogenic Ras. Drosophila uev1a mutants were lethal, not viable (see Lines 131-133), and germline-specific knockdown of uev1a (nos>uev1a-RNAi) caused female sterility without inducing tumors. These findings suggest that Uev1A lacks tumor-suppressive activity in the Drosophila female germline in the absence of Ras-driven tumors. We will revise the manuscript to prevent misinterpretation. Furthermore, we will investigate whether depletion of UBE2V1, UBE2V2, or both promotes oncogenic KRAS-driven overgrowth in human cancer cells.

      (4) A critical part of the model does not make sense. CycA is a key part of their model, but they do not show CycA protein expression in WT egg chambers or in their over-expression models (nos.RasV12 or bam>RasV12). Based on Lilly and Spradling 1996, Cyclin A is not expressed in germ cells in region 2-3 of the germarium; whether CycA is expressed in nurse cells in later egg chambers is not shown but is critical to document comprehensively.

      We appreciate this critical comment. CycA is a key cyclin that partners with Cdk1 to promote cell division (Edgar and Lehner, 1996). Notably, nurse cells are post-mitotic endocycling cells (Hammond and Laird, 1985) and typically do not express CycA (Lilly and Spradling, 1996) (see the last sentence, page 2518, paragraph 3). However, their death induced by oncogenic Ras<sup>G12V</sup> is significantly suppressed by monoallelic deletion of either cycA or cdk1 (Zhang et al., 2024). Conversely, ectopic CycA expression in nurse cells triggers their death (Figure 2C, 2D). These findings suggest that polyploid nurse cells exhibit high sensitivity to aberrant division-promoting stress, which may represent a distinct form of cellular stress unique to polyploid cells. To further test our model, we will compare CycA expression levels in normal nurse cells versus those undergoing oncogenic Ras<sup>G12V</sup>-induced cell death.

      (5) The authors should provide more information about the knowledge base of uev1a and its homologs in the introduction.

      Thanks for this suggestion. We will include this information in the introduction of the revised manuscript.

      Reviewer #2 (Public review):

      Summary:

      The authors performed a genetic screen using deficiency lines and identified Uev1a as a factor that protects nurse cells from Ras<sup>G12V</sup>-induced cell death. According to a previous study from the same lab, this cell death is caused by aberrant mitotic stress due to CycA upregulation (Zhang et al.). This paper further reveals that Uev1a forms a complex with APC/C to promote proteasome-mediated degradation of CycA.

      In addition to polyploid nurse cells, the authors also examined the effect of Ras<sup>G12V</sup>-overexpression in diploid germline cells, where Ras<sup>G12V</sup>-overexpression triggers active proliferation, not cell death. Uev1a was found to suppress its overgrowth as well.

      Finally, the authors show that the overexpression of the human homologs, UBE2V1 and UBE2V2, suppresses tumor growth in human colorectal cancer xenografts and cell lines. Notably, the expression of these genes correlates with the survival of colorectal cancer patients carrying the Ras mutation.

      Strength:

      This paper presents a significant finding that UBE2V1/2 may serve as a potential therapy for cancers harboring Ras mutations. The authors propose a fascinating mechanism in which Uev1a forms a complex with APC/C to inhibit aberrant cell cycle progression.

      We greatly appreciate these comments.

      Weakness:

      The quantification of some crucial experiments lacks sufficient clarity.

      Thanks for highlighting this issue. We will provide requested details regarding these quantification data in the revised manuscript.

      References

      Edgar, B.A., and Lehner, C.F. (1996). Developmental control of cell cycle regulators: a fly's perspective. Science 274, 1646-1652.

      Hammond, M.P., and Laird, C.D. (1985). Chromosome structure and DNA replication in nurse and follicle cells of Drosophila melanogaster. Chromosoma 91, 267-278.

      Lilly, M.A., and Spradling, A.C. (1996). The Drosophila endocycle is controlled by Cyclin E and lacks a checkpoint ensuring S-phase completion. Genes Dev 10, 2514-2526.

      Zhang, Q., Wang, Y., Bu, Z., Zhang, Y., Zhang, Q., Li, L., Yan, L., Wang, Y., and Zhao, S. (2024). Ras promotes germline stem cell division in Drosophila ovaries. Stem Cell Reports 19, 1205-1216.

    1. Reviewer #1 (Public review):

      Summary:

      The authors confirmed earlier findings that AVP influences α and β cells differently, depending on glucose concentrations. At substimulatory glucose levels, AVP combined with forskolin - an activator of cAMP -did not significantly stimulate β cells, although it did activate α cells. Once glucose was raised to stimulatory levels, β cells became active, and α cell activity declined, indicating glucose's suppressive effect on α cells and permissive effect on β cells. Under physiological glucose levels (8-9 mM), forskolin enhanced β-cell calcium oscillations, and AVP further modulated this activity. However, AVP's effect on β cells was variable across islets and did not significantly alter AUC measurements (a combined indicator of oscillation frequency and duration). In α cells, forskolin and AVP led to increased activity even at high glucose levels, suggesting that α cells remain responsive despite expected suppression by insulin and glucose.

      Experiments with physiological concentrations of epinephrine suggest that AVP does not operate via Gs-coupled V2 receptors in β cells, as AVP could not counteract epinephrine's inhibitory effects. Instead, epinephrine reduced β cell activity while increasing α cell activity through different G-protein-coupled mechanisms. These results emphasize that AVP can potentiate α-cell activation and has a nuanced, context-dependent effect on β cells.

      The most robust activation of both α and β cells by AVP occurred within its physiological osmo-regulatory range (~10-100 pM), confirming that AVP exerts bell-shaped concentration-dependent effects on β cells. At low concentrations, AVP increased β cell calcium oscillation frequency and reduced "halfwidths"; high concentrations eventually suppressed β cell activity, mimicking the muscarinic signaling. In α cells, higher AVP concentrations were required for peak activation, which was not blunted by receptor inactivation within physiological ranges.

      Attempting to further dissect the role of specific AVP receptors, the authors designed and tested peptide ligands selective for V1b receptors. These included a selective V1b agonist; a V1b agonist with antagonist properties at V1a and oxytocin receptors; and a selective V1a antagonist. In pancreatic slices, these peptides seem to replicate AVP's effects on Ca²⁺ signaling, although responses were highly variable, with some islets showing increased activity and others no change or suppression. The variability was partly attributed to islet-specific baseline activity, and the authors conclude that AVP and V1b receptor agonists can modulate β cell activity in a state-dependent manner, stimulating insulin secretion in quiescent cells and inhibiting it in already active cells.

      Strengths:

      Overall, the study is technically advanced and provides useful pharmacological tools. However, the conclusions are limited by a lack of direct mechanistic and functional data. Addressing these gaps through a combination of signaling pathway interrogation, functional hormone output, genetic validation, and receptor localization would strengthen the conclusions and reduce the current (interpretive) ambiguity.

      Weaknesses:

      (1) The study is entirely based on pharmacological tools. Without genetic models, off-target effects or incomplete specificity of the peptides cannot be fully ruled out.

      (2) Despite multiple claims about β cell activation or inhibition, the functional output - insulin secretion - is weakly assessed, and only in limited conditions. This aspect makes it very hard to correlate calcium dynamics with physiological outcomes.

      (3) Insulin and glucagon secretion assays should be provided; the authors should measure hormone release in parallel with Ca2+ imaging, using perifusion assays, especially during AVP ramp and peptide ligand applications.

      Additionally, there is no standardization of the metabolic state of islets. The authors should consider measuring islet NAD(P)H autofluorescence or mitochondrial potential (e.g., using TMRE) to control for metabolic variability that may affect responsiveness.

      (4) There is a high degree of variability in response to AVP and V1b agonists across islets (activation, no effect, inhibition). Surprisingly, the authors do not fully explore the cause of this heterogeneity (whether it is due to receptor expression differences, metabolic state, experimental variability, or other conditions).

      (5) There is no validation of V1b receptor expression at the protein or mRNA level in α or β cells using in situ hybridization, immunohistochemistry, or spatial transcriptomics.

      (6) AVP effects are described in terms of permissive or antagonistic effects on cAMP (especially in relation to epinephrine), but direct measurements of cAMP in α and β cells are not shown, weakening these conclusions. The authors should use Epac-based cAMP FRET sensors in α and β cells to monitor the interaction between AVP, forskolin, and epinephrine more conclusively.

      (7) Single-islet transcriptomics or proteomics (also to clarify variability) should be provided to analyze receptor expression variability across islets to correlate with response phenotypes (activation vs inhibition). Alternatively, the authors could perform calcium imaging with simultaneous insulin granule tracking or ATP levels to assess islet functional states.

      (8) While the study implies AVP acts through V1b receptors on β cells, the signaling downstream (e.g., PLC activation, IP3R isoforms involved) is simply inferred but not directly shown.

      (9) The interpretation that IP3R inactivation (mentioned in the title!) underlies the bell-shaped AVP effect is just hypothetical, without direct measurements. Assays in β (and/or α)-cell-specific V1b KO mice and IP3R KO mice must be provided to support these speculations.

    2. Reviewer #2 (Public review):

      Summary:

      In this paper, Drs. Kercmar, Murko, and Bombek make a series of observations related to the role of AVP in pancreatic islets. They use the pancreatic slice preparation that their group is well known for. The observations on the slide physiology are technically impressive. However, I am not convinced by the conclusions of this manuscript for a number of reasons. At the core of my concern is perhaps that this manuscript appears to be motivated to resolve 'controversies' surrounding the actions of AVP on insulin and glucagon secretion. This manuscript adds more observations, but these do not move the field forward in improving or solidifying our mechanistic understanding of AVP actions on islets. A major claim in this manuscript is the beta cell expression of the V1b Receptor for AVP, but the evidence presented in this paper falls short of supporting this claim. Observations on the activation of calcium in alpha cells via V1b receptor align with prior observations of this effect.

      I have focused my main concerns below. I hope the authors will consider these suggestions carefully - please be assured that they were made with the intent to support the authors and increase the impact of this work.

      Strengths:

      The main strength of this paper is the technical sophistication of the approach and the analysis and representation of the calcium traces from alpha and beta cells.

      Weaknesses:

      (1) The introduction is long and summarizes a substantive body of literature on AVP actions on insulin secretion in vivo. There are a number of possible explanations for these observations that do not directly target islet cells. If the goal is to resolve the mechanistic basis of AVP action on alpha and beta cells, the more limited number of papers that describe direct islet effects is more helpful. There are excellent data that indicate that the actions of AVP are mediated via V1bR on alpha cells and that V1bR is a) not expressed by beta cells and b) does not activate beta cell calcium at all at 10 nM - which is the same concentration used in this paper (Figure 4G) for peak alpha cell Ca2+ activation (see https://doi.org/10.1016/j.cmet.2017.03.017; cited as ref 30 in the current manuscript).

      (2) We know from bulk RNAseq data on purified alpha, beta, and delta cells from both the Huising and Gribble groups that there is no expression of V2a. I will point you to the data from the Huising lab website published almost a decade ago (http://dx.doi.org/10.1016/j.molmet.2016.04.007) - which is publicly available and can be used to generate figures (https://huisinglab.com/data-ghrelin-ucsc/index.html). They indicate the absence of expression of not only AVP2 receptors anywhere in the islet, but also the lack of expression of V1bra, V1brb, and Oxtr in beta cells. Instead of the detailed list of expression of these 4 receptors elsewhere in the body, it would be more directly relevant to set up their pancreatic slice experiments to summarize the known expression in pancreatic islets that is publicly available. It would also have helped ground the efforts that involved the generation of the V1aR agonist and V2R antagonist, which confirm these known AVP/OXT receptor expression patterns.

      (3) Importantly, the lack of V1br from beta cells does not invalidate observations that AVP affects calcium in beta cells, but it does indicate that these effects are mediated a) indirectly, downstream of alpha cell V1br or b) via an unknown off-target mechanism (less likely). The different peak efficacies in Figure 4G would also suggest that they are not mediated by the same receptor.

      (4) The rationale for the use of forskolin across almost all traces is unclear. It is motivated by a desire to 'study the AVP dependence of both alpha and beta cells at the same time'. As best as I can determine, the design choice to conduct all studies under sustained forskolin stimulation is related to the permissive actions of AVP on hormone secretion in response to cAMP-generating stimuli. The permissive actions by AVP that are cited are on hormone secretion, which in many cell types requires activation of both calcium and cAMP signaling. Whether the activation of V1br and subsequent calcium response is permitted by cAMP is unclear. I believe the argument the authors are making here is that the activation of beta cell calcium by AVP is permitted by forskolin. i.e., the cAMP stimulated by it in beta cells. However, the design does not account for the elevation of cAMP in alpha cells and subsequent release of glucagon, particularly upon co-stimulation with AVP, which permits glucagon release by activating a calcium response in alpha cells. This glucagon could then activate beta cells. If resolving the mechanism of action is the goal, often less is more. The activation of Gaq-mediated calcium is not cAMP dependent (although the downstream hormone secretion clearly often is). As was shown, AVP does not activate calcium in beta cells in the absence of cAMP. The experiments in Figures 1, 2, and 4 should have been completed in the absence of cAMP first.

      (5) It is unexpected that epinephrine in Figure 2 does not activate the alpha cell calcium? A recent paper from the same group (Sluga et al) shows robust calcium activation in alpha cells in a similar prep by 1 nM epinephrine, which is similar to the dose used here.

      (6) Figure 8 suggests a pharmacological activation of beta cell V1bR in the low pM range. How do the authors reconcile this comparison with the apparent absence of an effect of AVP stimulation at low pM to low nM doses in beta cells (Figure 4A)? I note that there are changes over time with sustained beta cell stimulation with 8 mM glucose, but these changes are relatively subtle, gradual, and quite likely represent the progression of calcium behaviors that would have occurred under sustained glucose, irrespective of these very low AVP concentrations. I will note that the Kd of the V1bR for AVP is around 1 nM, with tracer displacement starting around 100 pM according to the data in figure 5B, which is hard to reconcile with changes in beta cell calcium by AVP doses that start 10-100-fold lower than this dose at 1 and 10 pM (Figure 8).

    3. Author response:

      We sincerely thank the reviewers and editors for their thoughtful and constructive evaluation of our manuscript and their recognition of its technical strengths, including advanced spatio-temporal Ca2+ imaging, image processing, and the rational design of selective AVP receptor ligands. We appreciate their acknowledgement that our study contributes to the understanding of glucose-dependent AVP effects in pancreatic islet physiology. Their comments will guide us to refine the scope of our work, which focuses on how α and β cells respond to AVP under varying glucose and hormonal conditions, rather than on linear correlations between the function and transcript levels in individual cells or metabolic profiles in individual cell. Most of the reviewers´ concerns and proposed remedies reflect a reductionist framework, for which we believe cannot not fully account for emergent behavior within the islet collective. As we and others have shown, islet cells do not behave in isolation; their responses often depend on the state of the entire cell population(1, 2). This means that even under identical experimental conditions, responses can differ depending on the islet’s current state. These patterns are not random, but reflect how the islet integrates signals dynamically(3, 4).

      To take advantage of both the systems and molecular side, we do plan to address several of the reviewers' suggestions with new experiments and analyses:

      First, we will add hormone, specifically glucagon, secretion assays to support our conclusions on α cell responses and possible paracrine effects. Second, we will include a targeted transcript analysis of V1bR using RNAscope and extend the pharmacological characterization of downstream signaling using selective agonists and inhibitors. Third, we will clarify the rationale for using forskolin, and added new experiments using GLP-1 analogues to selectively increase cAMP in β cells, allowing us to examine direct AVP effects. And fourth, we will reinforce presence of emergency and that variability in islet responses is not experimental noise, but a hallmark of the collective, non-linear behavior of the islet cell collective, which should later drive a rethinking of experimental designs and the interpretation of pharmacological responses. In conclusion, we believe that our study provides new insights into AVP modulation in pancreatic islets and highlights the importance of context-dependent responses in α and β cells. We are grateful for the opportunity to revise our manuscript and look forward to further strengthening it further through the review process.

      (1) Jin E, Briggs JK, Benninger RKP, Merrins MJ. Glucokinase activity controls peripherally-located subpopulations of β-cells that lead islet Ca2+ oscillations. eLife Sciences Publications, Ltd; 2025.

      (2) Korošak D, Jusup M, Podobnik B, Stožer A, Dolenšek J, Holme P, et al. Autopoietic Influence Hierarchies in Pancreatic β Cells. Phys Rev Lett. 2021;127(16):168101.

      (3) Ball P. How life works : a user's guide to the new biology. Chicago: The University of Chicago Press; 2023. 541 pages p.

      (4) Fancher S, Mugler A. Fundamental Limits to Collective Concentration Sensing in Cell Populations. Phys Rev Lett. 2017;118(7):078101.

    1. Reviewer #1 (Public review):

      Summary

      In this manuscript, the authors introduce Gcoupler, a Python-based computational pipeline designed to identify endogenous intracellular metabolites that function as allosteric modulators at the G protein-coupled receptor (GPCR) - Gα protein interface. Gcoupler is comprised of four modules:

      I. Synthesizer - identifies protein cavities and generates synthetic ligands using LigBuilder3

      II. Authenticator - classifies ligands into high-affinity binders (HABs) and low-affinity binders (LABs) based on AutoDock Vina binding energies

      III. Generator - trains graph neural network (GNN) models (GCM, GCN, AFP, GAT) to predict binding affinity using synthetic ligands

      IV. BioRanker - prioritizes ligands based on statistical and bioactivity data

      The authors apply Gcoupler to study the Ste2p-Gpa1p interface in yeast, identifying sterols such as zymosterol (ZST) and lanosterol (LST) as modulators of GPCR signaling. Our review will focus on the computational aspects of the work. Overall, we found the Gcoupler approach interesting and potentially valuable, but we have several concerns with the methods and validation that need to be addressed prior to publication/dissemination.

      (1) The exact algorithmic advancement of the Synthesizer beyond being some type of application wrapper around LigBuilder is unclear. Is the grow-link approach mentioned in the methods already a component of LigBuilder, or is it custom? If it is custom, what does it do? Is the API for custom optimization routines new with the Synthesizer, or is this a component of LigBuilder? Is the genetic algorithm novel or already an existing software implementation? Is the cavity detection tool a component of LigBuilder or novel in some way? Is the fragment library utilized in the Synthesizer the default fragment library in LigBuilder, or has it been customized? Are there rules that dictate how molecule growth can occur? The scientific contribution of the Synthesizer is unclear. If there has not been any new methodological development, then it may be more appropriate to just refer to this part of the algorithm as an application layer for LigBuilder.

      (2) The use of AutoDock Vina binding energy scores to classify ligands into HABs and LABs is problematic. AutoDock Vina's energy function is primarily tuned for pose prediction and displays highly system-dependent affinity ranking capabilities. Moreover, the HAB/LAB thresholds of -7 kcal/mol or -8 kcal/mol lack justification. Were these arbitrarily selected cutoffs, or was benchmarking performed to identify appropriate cutoffs? It seems like these thresholds should be determined by calibrating the docking scores with experimental binding data (e.g., known binders with measured affinities) or through re-scoring molecules with a rigorous alchemical free energy approach.

      (3) Neither the Results nor Methods sections provide information on how the GNNs were trained in this study. Details such as node features, edge attributes, standardization, pooling, activation functions, layers, dropout, etc., should all be described in detail. The training protocol should also be described, including loss functions, independent monitoring and early stopping criteria, learning rate adjustments, etc.

      (4) GNN model training seems to occur on at most 500 molecules per training run? This is unclear from the manuscript. That is a very small number of training samples if true. Please clarify. How was upsampling performed? What were the HAB/LAB class distributions? In addition, it seems as though only synthetically generated molecules are used for training, and the task is to discriminate synthetic molecules based on their docking scores. Synthetic ligands generated by LigBuilder may occupy distinct chemical space, making classification trivial, particularly in the setting of a random split k-folds validation approach. In the absence of a leave-class-out validation, it is unclear if the model learns generalizable features or exploits clear chemical differences. Historically, it was inappropriate to evaluate ligand-based QSAR models on synthetic decoys such as the DUD-E sets - synthetic ligands can be much more easily distinguished by heavily parameterized ligand-based machine learning models than by physically constrained single-point docking score functions.

      (5) Training QSAR models on docking scores to accelerate virtual screening is not in itself novel (see here for a nice recent example: https://www.nature.com/articles/s43588-025-00777-x), but can be highly useful to focus structure-based analysis on the most promising areas of ligand chemical space; however, we are perplexed by the motivation here. If only a few hundred or a few thousand molecules are being sampled, why not just use AutoDock Vina? The models are trained to try to discriminate molecules by AutoDock Vina score rather than experimental affinity, so it seems like we would ideally just run Vina? Perhaps we are misunderstanding the scale of the screening that was done here. Please clarify the manuscript methods to help justify the approach.

      (6) The brevity of the MD simulations raises some concerns that the results may be over-interpreted. RMSD plots do not reliably compare the affinity behavior in this context because of the short timescales coupled with the dramatic topological differences between the ligands being compared; CoQ6 is long and highly flexible compared to ZST and LST. Convergence metrics, such as block averaging and time-dependent MM/GBSA energies, should be included over much longer timescales. For CoQ6, the authors may need to run multiple simulations of several microseconds, identify the longest-lived metastable states of CoQ6, and perform MM/GBSA energies for each state weighted by each state's probability.

    1. Reviewer #2 (Public review):

      Tittelmeier et al. investigated the role of sphingolipid (SL) metabolism in the maintenance of endolysosomal vesicle integrity. They find that both impaired SL biosynthesis and degradation in C. elegans, decrease the fluidity of endolysosomal membranes and promote their rupture, while it has little effect on plasma membrane fluidity. Endolysosomal membrane fluidity is also negatively affected in human cells upon knockdown (KD) of a gene (SPHK2) involved in the SL degradation pathway. Aggregated forms of tau in both models (C. elegans and human cells) can also cause rigidification of the endolysosomal membrane, with SL homeostasis disruption having an additive effect, exacerbating endolysosomal rupture. Notably, KD of SPHK2 also increased the formation of tau foci, suggesting that compromised endolysosomal integrity may promote tau aggregation. These data provide a clearer understanding of how genetic manipulation of SL metabolism affects endolysosomal membranes and their rigidification in the context of tau aggregation. Supplementation of polyunsaturated fatty acids (PUFAs), which has a beneficial effect on Alzheimer's patients, improved membrane fluidity and reduced tau propagation in human cells and tau-associated neurotoxicity in C. elegans, suggesting a possible mechanism of action.

      Overall, the conclusions of this paper are supported by the data, with a few aspects requiring further clarification and elaboration.

      (1) A reference to Figure S2E-G, which shows that KD of SL biosynthesis genes do not affect the plasma membrane, is missing from the main text.

      (2) In Figure 3C, lipofectamine alone shows that it increases membrane rigidity (increased GP values), not membrane fluidity.

      (3) In Figure 3F, the EV cntl condition expressing F3:mCh tau should have increased LGALS3 foci compared to the mCh EV cntl according to Ref (20) and its Figure 2G (at least for Day 5 animals), which would be indicative of the tau spreading in hypodermal tissue. What C. elegans age was examined in Figure 3F? Can the authors provide evidence of the transmission of the F3:mCh tau from the touch receptor neurons to the hypodermis in the EV [similar to Figure 2C & D from Ref (20)] and compare it to the KDs? Otherwise, it seems that KD of SL genes impacts not only endolysosomal rupture but significantly affects tau accumulation/spreading as well (e.g., shown later in HEK cells, where SPHK2 KD increases the formation of tau-Venus foci).

      (4) Sphingolipids are essential membrane components and signaling molecules. Does KD of SL genes in C. elegans and the subsequent endolysosomal rupture cause any major, intermediate, or minor defects/phenotypes (in non-aggregation prone models, w/t..)?

    2. Reviewer #3 (Public review):

      Summary:

      The authors set off with an analysis of the lysosomal integrity upon knockdown of genes of the sphingolipid metabolic pathway that they identified in a previous (yet unpublished) work of an RNA screen using a new C. elegans Tau model. They then used cell culture and C. elegans experiments to study the link between lysosomal rupture and Tau propagation.

      Strengths:

      The authors use two complementary model systems and use probes to assess membrane rigidity that allow a quick assessment of the membrane dynamics and offer the opportunity to treat the cells with lipids, RNAi. Tau seeds, etc.

      Weaknesses:

      The main weakness is that this work builds on not-yet-peer-reviewed manuscript that established a new C. elegans Tau model and RNAi screen that aimed to identify genes involved in the propagation of Tau.

      This reviewer misses essential information of the C. elegans Tau strain (not included in the method section): e.g., promoter used for the expression, information on the used Tau variant, expression pattern, and aggregation, etc.

      Throughout the study, I missed data on:

      (1) Effect of the knockdown on Tau expression, localisation (with lysosomal membrane?), aggregation, and proteotoxicity. The effect of the RNAi-mediated knockdown could also simply lead to a reduced expression of Tau that, in turn, leads to suppressed propagation.

      (2) A quantification of RNAi knockdown is needed to judge the efficiency of the RNAi, in particular for the combinatorial RNAi experiments involving 2 and even 4 genes in parallel. Ideally, these analyses should be validated with mutants for these genes.

      Further:

      (3) Figure 4 H, I: Would Tau also aggregate in the absence of externally added Tau?

      (4) How specific is the effect for Tau? It would help if the authors could assess other amyloid proteins.

      (5) The connection between sphingolipids and AD is not new. See He et al, 2010, Neurobiol. Aging + numerous publications and also not between Tau seeding and lysosomal rupture: Rose et al., PNAS 2024 (that has been cited by the authors).

    1. TrailHub@TrailHub1·Nov 2, 2021Annotations are key @TrailMarks vision. experimented with it https://mindgraph.co/hpth/ ages ago I share @dwhly's vision "just name it and it's created. So powerful. It should be everywhere and in everything." Wiky 4 naming #Indiehub 4 over web interoperability via links!

      4 indyhub

    1. Reviewer #2 (Public review):

      The manuscript entitled "Structure of an oxygen-induced tubular nanocompartment in Pyrococcus furiosus" by Wenfei Song et al. employs whole-cell mass spectrometry and cryo-EM (including tomography, helical reconstruction, and single-particle analysis) to investigate the structure and function of the oxidoreductase Rubrerythrin (Rbr) from Pyrococcus furiosus. The study reports that under oxidative stress, Rbr forms a tubular structure, in contrast to its behaviour under anaerobic conditions. Authors characterized oxidoreductase Rubrerythrin (Rbr) from Pyrococcus furiosus under anaerobic conditions and formed a tubular structure when induced with oxidative stress. This study is well-designed. However, I have several questions related to the experimental design and the results obtained from those experiments, which are listed below.

      (1) The authors have mentioned that "Under aerobic conditions, Rbr levels are 3 to 13 times higher compared to anaerobic conditions (Figures 1a-d)." Also, they performed whole-cell mass spec to measure the overexpression of the Rbr enzyme under anaerobic conditions. Thus, from the above statement, I consider the authors' claim that P. furiosus cells were cultured under anaerobic conditions and then exposed to oxidative stress. While cell growth under anaerobic conditions appears perfectly fine, the authors conducted the rest of the experiment under aerobic conditions during mass spectrometry and cryo-EM sample preparation. As a baseline, the author first grew the cells in their preferred anaerobic environment and also imaged the same cells that were exposed to air (aerobic) after anaerobic growth. The cell growth in anaerobic conditions is perfectly fine. But how did authors make sure that during anaerobic conditions, the Rbr enzyme is not expressed or not formed? As a control experiment, authors should demonstrate that during mass spec and cryo-EM sample preparations, cells are not exposed to air or maintained in an anaerobic environment. From anaerobic conditions, whenever cells were selected for spec and cryo-EM, cells were exposed to O2, and definitely controlled cells were not in anaerobic conditions anymore.

      The authors collected P. furiosus wild-type or Rbr knockout cells in an anaerobic hood, but after that, they centrifuged the cells and plunged them using a Vitrobot. Are the instrument, centrifuge, and Vitrobot kept in an anaerobic environment? Recently, a few studies (anaerobic plunge-freezing in cryo-electron microscopy, Cook et al. (2024), Hands-Portman and Bakker (2022) DOI: 10.1039/D2FD00060A ) have mentioned the anaerobic plunge freeze setup for protein sample or cell freezing. I guess the authors did not use that setup. In these circumstances, the cell is already exposed to O2 during centrifugation and Vitrobot freezing. How were the control experiments properly performed in anaerobic conditions? A similar argument is true for Lamella grid preparation, where the enzyme was already exposed to O2, and single-particle grid preparation, where the purified enzyme is already exposed to O2. How were the control experiments properly performed in anaerobic conditions?

      (2) It is important to provide evidence that the overexpressed protein is actually in an anaerobic condition and is later induced with more O2. Also, authors should confirm biochemically that the overexpressed protein in their desired protein "oxidoreductase Rubrerythrin (Rbr)". No biochemical data were provided in this manuscript. During single-particle analysis, the authors had to purify the protein sample and confirm that these were their desired protein samples. No biochemical or biophysical experiments were performed to confirm that the overexpressed protein is the desired protein.

      (3) Figure 3, the atomic model looks different in all four tetramers. However, I have fitted the atomic model into the cryo-EM map, which looks reasonable. However, it will be easier for the reader to evaluate the model if the authors show different orientations of the atomic model, as well as if the authors could show that the atomic model fits the cryo-EM map.

      (4) How did the authors select initial particle sets like 24 lakhs when forming helices and not forming isolated particles?

      (5) The authors proposed a model for electron transfer upon oxidative stress. However, the data is not convincing that VLP is surrounded by Rbr and forms a tube-like structure. Generally, VLP is a sphere-like structure, and Rbr can form a tube-like structure when it interacts with spherical VLP. Rbr will surround VLP, and it will form a Rbr-decorated sphere-like structure.

      (6) It will also be important to comment on the diameter of Oxidative stress-induced tubules (OSITs) and 3D reconstruction and/or helical reconstruction of purified protein samples. The spherical cyan densities within the tube are not very clear. If VLP is surrounded by Rbr (Figure 4), extra Rbr densities will be observed on VLP in the tomogram (in Figure 1). However, in the tomogram, VLP is inside Oxidative stress-induced tubules (OSITs). Figure 1 is a contradicting Figure 4. The authors should explain it properly.

      (7) The authors performed helical reconstruction. Where is the Layer line calculation in helical reconstruction, and how do authors identify helical parameters for reconstruction?

      (8) The authors used an extremely confusing methodology, which was very difficult to follow. The authors performed tomography, helical reconstruction, and single-particle analysis. Why did the authors need 3 different image processing methods to resolve structures that are not clear to me? The authors should also show the proper fitting between the map and the model. In Supplemental Figure 6c, the overall fitting of the subdomain looks ok. However, many peptide chains and side chains are not fitted properly in the EM density map. It will be helpful to show proper side chain fitting. In Supplementary Fig. 6a, the authors binned the data (Bin 8 or Bin 2) but did not mention when they unbinned the data for data processing. Also, the authors implemented C2 symmetry during local refinement. Why do authors suddenly use C2 symmetry expansion?

      Minor Comments:

      (1) The authors should properly show a schematic diagram of the enzyme subdomains. It will help to understand interactions or tetrameric assembly.

      (2) The introduction is poorly written. It will really be helpful for the reader if the authors provide a proper introduction.

      (3) The atomic model did not fit into the cryo-EM, so it was hard to determine the overall fitting.

      (4) 17.1A pixel size? It's surprising.

      (5) It will be better to calculate local resolution and show the map's angular distribution. It is obvious that resolution at the peripheral region will be poorer than core region. Therefore, it will be better to calculate local resolution. Additionally, authors should show the map to model fitting.

    1. Reviewer #2 (Public review):

      Summary:

      This manuscript addresses the gap in knowledge related to the cardiac function of the S-denitrosylase SNO-CoA Reductase 2 (SCoR2; product of the Akr1a1 gene). Genetic variants in SCoR2 have been linked to cardiovascular disease, yet their exact role in the heart remains unclear. This paper demonstrates that mice deficient in SCoR2 show significant protection in a myocardial infarction (MI) model. SCoR2 also affected ketolytic energy production, antioxidant levels, and polyol balance through the S-nitrosylation of crucial metabolic regulators.

      Strengths:

      (1) Addresses a well-defined gap in knowledge related to the cardiac role of SNO-CoA Reductase 2. Besides the in-depth case for this specific player, the manuscript sheds more light on the links between S-nitrosylation and metabolic reprogramming in the heart.

      (2) Rigorous proof of requirement through the combination of gene knockout and in vivo myocardial ischemia/reperfusion.

      (3) Identification of precise Cys residue for SNO-modification of BDH1 as SCoR2 target in cardiac ketolysis

      Weaknesses:

      (1) The experiments with BDH1 stability were performed in mutant 293 cells. Was there a difference in BDH1 stability in myocardial tissue or primary cardiomyocytes from SCoR2-null vs -WT mice? The same question extends to PKM2.

      (2) In the absence of tracing experiments, the cross-sectional changes in ketolysis, glycolysis, or polyol intermediates presented in Figures 4 and 5 are suggestive at best. This needs to be stressed while describing and interpreting these results.

      (3) The findings from human samples with ischemic and non-ischemic cardiomyopathy do not seem immediately or linearly in line with each other and with the model proposed from the KO mice. While the correlation holds up in the non-ischemic cardiomyopathy (increased SNO-BDH1, SNO-PKM2 with decreased SCoR2 expression), how do the authors explain the decreased SNO-BDH1 with preserved SCoR2 expression in ischemic cardiomyopathy? This seems counterintuitive as activation of ketolysis is a quite established myocardial response to ischemic stress. It may help the overall message clarity to focus the human data part on only NICM patients.

      (4) This issue is partially linked to point #(3). Currently, important evidence that is lacking is the demonstration of sufficiency for SCoR2 in S-nytrosylation of targets and cardiac remodeling. Does SCoR2 overexpression in the heart or isolated cardiomyocytes reduce S-nitrosylation of BDH1 and other targets, thus affecting heart function at baseline or under stress?

    1. Reviewer #1 (Public review):

      Summary:

      In this manuscript, Uphoff et al. propose a structural and mechanistic model in which the multidomain ECM protein SVEP1 enables Angiopoietin (ANG) binding to the orphan receptor TIE1, thereby promoting downstream receptor phosphorylation and signaling. Using AlphaFold-based modeling, the authors predict that the CCP20 domain of SVEP1 binds to TIE1, creating a composite surface that facilitates Angiopoietin association and TIE1 activation. The resulting ternary model (SVEP1-TIE1-ANG) offers a structural rationale for how SVEP1 converts TIE1 into a functional, ligand-responsive receptor. Additional models and biological assays suggest roles for other domains of SVEP1, such as CCP5-EGF-L7, although these interactions are predicted with low confidence. The authors interpret these findings as the first structural framework for how SVEP1 enables ANG-TIE1 signaling.

      Strengths:

      (1) The central hypothesis - that SVEP1 enables ANG binding to the orphan receptor TIE1 - is biologically compelling and addresses an important question in vascular biology.

      (2) The AlphaFold-predicted ternary complex (SVEP1-TIE1-ANG) is plausible, high-confidence, and structurally consistent with prior functional data (e.g., poly-Ala scanning from Sato-Nishiuchi et al.).

      (3) The authors' model offers a potential explanation for the previously observed role of SVEP1 in enhancing ANG signaling through TIE1, and may represent the first structural insight into TIE1's transition from orphan to ligand-activated receptor.

      (4) The potential clinical implication - that a combinatorial ligand (ANG+SVEP1) can activate TIE1- could have translational relevance for vascular leak and inflammatory disease.

      Weaknesses:

      (1) Lack of structural validation and mechanistic follow-up:
Despite the promising AlphaFold model, there are no figures of the predicted interface, no residue-level interactions shown, no ipTM values reported, and no experimental follow-up to test the interface. PAE plots are incorrectly used as confidence justifications, which is not appropriate for complex predictions.

      (2) Biophysical validation is missing:
No surface plasmon resonance (SPR), ITC, or biochemical assays are included to confirm ternary complex formation or quantify binding kinetics. Given the manuscript's structural focus, this is a major gap. For instance, an SPR experiment where ANG is immobilized, and TIE1 binding is measured {plus minus} SVEP1, would directly test the model. And allow direct comparison to ANG-TIE2.

      (3) Missed opportunity for mutagenesis-driven validation:
 The manuscript does not include any interface-targeted mutations, despite clear opportunities. For example, mutating T2595 in SVEP1 (to R) or mutating the TIE1-specific residues (residues PL 202-203 to LF) could strongly test the model and potentially reveal dominant-negative behaviors. E.g. A T2595 mutant should block ANG binding but not TIE1 binding.

      (4) Overinterpretation of weak models:
The additional AlphaFold model involving the CCP5-EGFL7 domains binding TIE1 has extremely low confidence (ipTM < 0.15) when reexamined by this reader and should not be emphasized. There is no biophysical evidence or binding data (SPR) to support this interaction, and its inclusion detracts from the much stronger CCP20 model.

      (5) Language around modeling is overstated and potentially misleading:
Terms like "unequivocal," "high-affinity," or "affirms strong binding" in reference to AlphaFold predictions are inappropriate. These are hypotheses -not confirmations - and must be tested at the biochemical level. This should be clarified throughout the manuscript to ensure non-experts do not misinterpret modeling confidence as binding affinity.

      (6) Negative stain EM data is not informative due to low resolution and lack of defined interfaces; unless replaced by higher-resolution Cryo-EM, this should be omitted. Better would be co-gel filtration, AUC, or SEC-MALLs with ANG-SVEP1-TIE1.

      (7) Disjointed narrative:
The manuscript presents a compelling mechanism involving CCP20-driven ANG binding to TIE1, but then becomes fragmented by introducing the low-confidence CCP5-EGFL7 model and speculative higher-order polymerization models that are not experimentally supported.

    2. Reviewer #2 (Public review):

      Uphoff and colleagues present the results of a study focused on characterizing the binding of SVEP1 to TIE1 along with Angiopoietin-2. Starting with computational prediction of SVEP1 binding to TIE1, the authors identify the region of SVEP1 that serves as a high-affinity ligand for TIE1. Advanced studies identify a weak secondary binding site within SVEP1 that appears to be sufficient but not necessary for its interaction with TIE1 based on in vivo rescue experiments. The most novel contribution of the manuscript seems to be the identification of angiopoietin-1 and -2 as co-factors that seem to enhance the binding of SVEP1 with TIE1 and impact downstream AKT signaling. They propose a complex in which SVEP1 binds to TIE1 and ANG2.

      Although the first set of results is essentially confirmatory, the identification of ANG-2 as a "co-factor" enhancing the binding of SVEP1 to TIE1 and associated downstream signaling (i.e., Figures 3 and 4) is novel and is of interest. However, the manuscript and its conclusions would greatly benefit from some clarifying details and additional experiments to ensure rigor and support specific claims.

    1. focus on four goals for reform that are drawn from my own research as well as that of others involving students living in poverty: 1. Understand and practice equitable decision making 2. Understand and respond to neighborhood conditions 3. Reduce class size for school-dependent students (i.e., for students who rely heavily on school for their academic, social, emotional, behavioral, and affective development) 4. Rethink and reform the inflexible, narrowed curriculum

      Effective education reform for students living in poverty must prioritize equitable decision-making, ensuring that policies reflect the diverse needs and lived experiences of marginalized communities. Addressing neighborhood conditions, reducing class sizes for school-dependent students, and expanding a rigid curriculum are essential steps toward creating environments where all learners can thrive. Together, these goals emphasize a holistic approach that recognizes the intersection of social, emotional, and academic factors in student success.

    1. Reviewer #1 (Public review):

      Engineering of AAV replication proteins may provide new insights into Parvoviral replication and potentially enable improved recombinant AAV vector yield when incorporated into the manufacturing process. Silberg and colleagues report an AAV Rep library, that is an interesting and powerful approach, however, the screening design and subsequent experiments lack rigor and ultimately the results are premature. Overall, the manuscript does not accurately describe state-of-the-art in the field and has significant shortcomings with experimental design/data analysis. Key concerns are noted below:

      The high enrichment of P19 variants in the library was likely an artifact of the fact they only transfected 20 ng of RepCap into their 5-plate preps. When such little Rep is provided, any boost in Rep expression levels will have a major on yield. When more RepCap is provided, 10 ug in their later evaluation, small changes in Rep expression are unlikely to have major impacts on yield. A more effective strategy would have been to transfect a normal amount of DNA and then utilize serial passaging through infectious cycling to account for cross packaging.

      Introduction:<br /> - There are 7 FDA approved AAV gene therapies.<br /> - The description of "shuffling" when citing Mietsczh et al is misapplied. The cited paper discusses rationally designed hybrids.<br /> - The graphic represents a hybrid capsid, but the focus is rep. As such, this should be depicted differently.

      Figures 1 and 2 are validation of previously published findings and general optimization of the experimental conditions. These do not provide the reader any new insight or information.

      In Figure 3: The experimental approach is limited. It is unclear how the subpooling of different conditions was performed. As mentioned above, their library transfection strategy will significantly bias the results. The enriched variants have not been evaluated - specifically, the enriched non-synonymous mutations have not been shown to yield higher titers when tested individually.<br /> In Figure 4: The claim is made that "several synonymous mutations within the p19 promoter region increase Rep DNA packaging activity." However, Figure 4c does not show statistically significant differences in support of this claim. Additional supporting data is needed. Further, Authors state that the synonymous mutations are near the P19 promoter. However, looking at the sequence shown in figure 4, their annotation of the P19 promoter is not correct and the mutations are actually within the P19 promoter. Relatedly, the authors note that mutations enriched in the p19 region include additional tetranucleotide repeats. No synthetic variants with additional GCTCs have been generated to test this hypothesis. Further, these results would benefit from a Western blot and transcript analysis to confirm Rep52/40, expression levels of constructs.

    1. Author response:

      The following is the authors’ response to the original reviews

      eLife Assessment

      This valuable study investigates prey capture by archer fish, showing that even though the visuomotor behavior unfolds very rapidly (within 40-70 ms), it is not hardwired; it can adapt to different simulated physics and different prey shapes. Although there was agreement that the model system, experimental design, and main hypothesis are certainly interesting, opinions were divided on whether the evidence supporting the central claims is incomplete. A more rigorous definition and assessment of "reflex speed", more detailed evidence of stimulus control, and a more detailed analysis of individual subjects could potentially increase confidence in the main conclusions.

      Thank you very much. There are several points that we had to absolutely make sure that they are very well understood. (1) Explaining in the best possible way the experiment with a fly sliding on top of a glass plate. Here, the virtual ballistic landing point can be calculated using simple high school physics. It turns out that this is where the fish turn to – even though the fly is not falling at all. Once this is understood it becomes clear that we can precisely measure latency and accuracy of the C-start turns. In the new version we explain this essential aspect in more detail and add an extra Figure (new Figure 2). This may, perhaps, help readers to notice this important background (previously covered in Fig. 1C). (2) The full experimental evidence that the VR method works is presented in more detail and all measurements necessary will be clear after the new Figure 2. They will however not be clear if this Figure is ignored. (3) We have rewritten the manuscript to make it easier to understand what we wanted to show, why we needed VR to proceed and why the archerfish highspeed decision lent itself so readily to tackle the problem. (4) We emphasize the importance of speed-accuracy tradeoffs in standard decision-making and also include data on the absence of such a relation in the archerfish highspeed decisions.

      So, in summary, we have emphasized what we wanted to show and what we did not want to show, we have rewritten the text to make it easier for future readers and we have tried to add more guidance to the figures. We do hope very much that the beauty of the quite unexpected findings is more easily visible to those who take the trouble of actually reading the paper.  

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      The authors test whether the archerfish can modulate the fast response to a falling target. By manipulating the trajectory of the target, they claim that the fish can modulate the fast response. While it is clear from the result that the fish can modulate the fast response, the experimental support for the argument that the fish can do it for a reflex-like behavior is inadequate.

      Please note that we have not simply tested whether archerfish can 'modulate the fast response'. We quantitatively test specific hypotheses on the rules used by the fish. For this the accuracy of the decisions is analyzed with respect to specific points that can be calculated precisely in each of the experiments. These points are shown on the figures and in the movies that were meant to illustrate this important aspect. We had to make sure that the way we calculate the predicted point(s) is made as clear as possible in the text. We added more text and separated the fundamentally important aspects in a separate Figure 2 to make it more difficult to overlook the fundamental aspects that lay the foundation for everything that follows.

      Strengths:

      Overall, the question that the authors raised in the manuscript is interesting.

      Thank you and we do hope very much that, with our revision, you will see the beauty of the findings.

      Weaknesses:

      (1) The argument that the fish can modulate reflex-like behavior relies on the claim that the archerfish makes the decision in 40 ms. There is little support for the 40 ms reaction time. The reaction time for the same behavior in Schlegel 2008, is 6070 ms, and in Tsvilling 2012 about 75 ms, if we take the half height of the maximum as the estimated reaction time in both cases. If we take the peak (or average) of the distribution as an estimation of reaction time, the reaction time is even longer. This number is critical for the analysis the authors perform since if the reaction time is longer, maybe this is not a reflex as claimed. In addition, mentioning the 40 ms in the abstract is overselling the result. The title is also not supported by the results.

      Although the minimum latency is indeed 40 ms (it can be slightly less: e.g., see the evidence in the paper, for instance the plots in the new Fig. 4) the paper's statements are not dependent on a specific number. Even if minimum latency was 100 ms (which it is not) the speed of the response and the absence of a speedaccuracy relation (now shown directly in Fig. 4) is what is of importance. To show this we have completely rewritten large parts of the manuscript.

      (2) A critical technical issue of the stimulus delivery is not clear. The frame rate is 120 FPS and the target horizontal speed can be up to 1.775 m/s. This produces a target jumping on the screen 15 mm in each frame. This is not a continuous motion. Thus, the similarity between the natural system where the target experiences ballistic trajectory and the experiment here is not clear. Ideally, another type of stimulus delivery system is needed for a project of this kind that requires fast-moving targets (e.g. Reiser, J. Neurosci.Meth. 2008). In addition, the screen is rectangular and not circular, so in some directions, the target vanishes earlier than others. It must produce a bias in the fish response but there is no analysis of this type.

      Please note that the new Fig. 3 (former Fig. 2) reports all the evidence that is needed to just show this and in a way that could in no way have been better. We have rewritten the text to explain what needs to be shown experimentally in order to be able to proceed, what critical tests were done and what results were obtained. We also add a short comment on another unsuccessful attempt that we have tried before.

      (3) The results here rely on the ability to measure the error of response in the case of a virtual experiment. It is not clear how this is done since the virtual target does not fall. How do the authors validate that the fish indeed perceives the virtual target as the falling target? Since the deflection is at a later stage of the virtual trajectory, it is not clear what is the actual physics that governs the world of the experiment. Overall, the experimental setup is not well designed.

      Understanding this aspect is essential. If the glass plate experiment is not thoroughly understood (new Fig. 2 with new text to emphasize that this is absolutely essential) nothing that follows makes any sense, including what is meant by the statement that the decision could be hardwired to ballistic motion.

      Reviewer #2 (Public review):

      Summary:

      This manuscript studies prey capture by archer fish, which observe the initial values of motion of aerial prey they made fall by spitting on them, and then rapidly turn to reach the ballistic landing point on the water surface. The question raised by the article is whether this incredibly fast decision-making process is hardwired and thus unmodifiable or can be adjusted by experience to follow a new rule, namely that the landing point is deflected from a certain amount of the expected ballistic landing point. The results show that the fish learn the new rule and use it afterward in a variety of novel situations that include height, side, and speed of the prey, and which preserve the speed of the fish's decision. Moreover, a remarkable finding presented in this work is the fact that fish that have learned to use the new rule can relearn to use the ballistic landing point for an object based on its shape (a triangle) while keeping simultaneously the 'deflected rule' for an object differing in shape (a disc); in other words, fish can master simultaneously two decisionmaking rules based on the different shape of objects.

      Strengths:

      The manuscript relies on a sophisticated and clever experimental design that allows changing the apparent landing point of a virtual prey using a virtual reality system. Several robust controls are provided to demonstrate the reliability and usefulness of the experimental setup.

      Overall, I very much like the idea conveyed by the authors that even stimuli triggering apparently hardwired responses can be relearned in order to be associated with a different response, thus showing the impressive flexibility of circuits that are sometimes considered mediating pure reflexive responses.

      Thank you so much for this precise assessment of what we have shown!

      This is the case - as an additional example - of the main component of the Nasanov pheromone of bees (geraniol), which triggers immediate reflexive attraction and appetitive responses, and which can, nevertheless, be learned by bees in association with an electric shock so that bees end up exhibiting avoidance and the aversive response of sting extension to this odorant (1), which is a fully unnatural situation, and which shows that associative aversive learning is strong enough to override preprogrammed responding, thus reflecting an impressive behavioral flexibility.

      That's very interesting, thanks and we are very happy to mention this important study in the revised version.

      Weaknesses:

      As a general remark, there is some information that I missed and that is mandatory in the analysis of behavioral changes.

      Firstly, the variability in the performances displayed. The authors mentioned that the results reported come from 6 fish (which is a low sample size). How were the individual performances in terms of consistency? Were all fish equally good in adjusting/learning the new rule? How did errors vary according to individual identity? It seems to me that this kind of information should be available as the authors reported that individual fish could be recognized and tracked (see lines 620-635) and is essential for appreciating the flexibility of the system under study.

      Secondly, the speed of the learning process is not properly explained. Admittedly, fish learn in an impressive way the new rule and even two rules simultaneously; yet, how long did they need to achieve this? In the article, Figure 2 mentions that at least 6 training stages (each defined as a block of 60 evaluated turn decisions, which actually shows that the standard term 'Training Block' would be more appropriate) were required for the fish to learn the 'deflected rule'. While this means 360 trials (turning starts), I was left with the question of how long this process lasted. How many hours, days, and weeks were needed for the fish to learn? And as mentioned above, were all fish equally fast in learning? I would appreciate explaining this very important point because learning dynamics is relevant to understanding the flexibility of the system.

      First, it is very important to keep the question in mind that we wanted to clarify: Does the system have the potential to re-tune the decisions to other non-ballistic relations between the input variables and the output? This would have been established if one fish was found capable of doing that. We have rewritten the introduction and discussion to specifically say what our aim was. We feel that the paper is already extremely long and difficult to understand (even after we tried very hard in this revision to explain everything in detail and as good as we could), requires the establishment of a method whose success was really unexpected and finding a degree of plasticity that we did not expect at all. We also have added a section in the discussion stating what we can, and we cannot say given the number of fish examined. For instance, we do not know if there are differences in the speed at which the different individuals mastered the new rules and if social learning could play a role to speed up the acquisition. That is a brilliant idea and we are very interested in checking this - but we wanted to stick with the (quite ambitious) goal of the present study.

      Reference:

      (1) Roussel, E., Padie, S. & Giurfa, M. Aversive learning overcomes appetitive innate responding in honeybees. Anim Cogn 15, 135-141, doi:10.1007/s10071011-0426-1 (2012).

      Thanks for this reference!

      Recommendations for the authors:

      Reviewer #1 (Recommendations for the authors):

      Minor comments:

      (1) What is the difference between Reinel, J. Exp. Bio. 2016 and the current study?

      Clearly in that study all objects were strictly falling ballistically, and latency and accuracy of the turn decisions were determined when the initial motion was not only horizontal but had an additional vertical component of speed. The question of that study was if the need to account to an additional variable (vertical speed) in the decision would affect its latency or accuracy. The study showed that also then archerfish rapidly turn to the later impact point. It also showed that accuracy and latency were not changed by the added degree of freedom.

      (2) How do Figures 2 F and G demonstrate that an accurate start is possible?

      See above.

      (3) Figure 4 is hard to follow, it is not clear what is presented and how it supports the claim that the new rule is represented in a way that allows immediate generalization.

      Yes, this is not at all an easy experiment. Briefly, fish were re-trained at only one height level and then are tested at other levels. The strategy is as in the experiments Schuster et al. 2004 Current Biology, Vol. 14, 1565–1568, Figure 5. We have changed text and Figure (new Figure 5) to show how the predictions were reached.

      Reviewer #2 (Recommendations for the authors):

      Minor remarks

      Lines 88-90: I was surprised to see that in this section, the authors did not mention the speed-accuracy trade-off off which has inspired numerous experiments in animal behavior (1). This could be used to back their point, namely, that speed comes with an apparent cost of a loss in accuracy.

      Yes, that is a crucial aspect that was completely missing even though it demonstrates a key aspect of 'standard' versus some 'highspeed' decisions! We definitely had to include it and also to show, directly under the conditions of our present experiments (in the new Fig. 4) the absence of a significant speedaccuracy relation for the archerfish highspeed decisions! Thank you very much for emphasizing this crucial aspect!

      Lines 182-184: Specify that this situation corresponds to the hatched bar in Figure (this can be specified in the caption of the figure, where the bar is not mentioned).

      Thanks!

      Lines 187-188: here and elsewhere (e.g. lines 224-225, etc), the error made by the fish is presented in cm (see Figure 2 where the inset shows how the error was computed). I wonder if it would not be more appropriate to present it in terms of the angular difference between the trajectory made by the fish and the food delivery location.

      Angles could also be used, but because of the large variation in initial distances (that we wanted to make sure that the fish had to capture a rule, allowing them to respond from various distances) another measure was used that we found somehow more natural: it is simply how close a fish would get to the landing point if it continued in the direction assumed after the turn. Although we describe how we defined accuracy we did not discuss why this measure was used in this (and many previous studies). We are very happy to add this. Please also note that running all tests based on angular errors (which we also have done throughout to ensure that the conclusions are independent on an arbitrary measure of the error) leads to no different conclusion. We have added a brief explanation in the text and in the new Fig. 2.

      Lines 299-323: Is it my impression or did fish have more trouble in generalizing their learned rule to the condition untrained larger height (see for instance red curves in Figures 4 D, E, G)? Could the authors elaborate on this point?

      We changed the code to make this more clear. The red curves (before marked A to highlight impact point option A) correspond to the errors to the ballistic impact point without deflection, so what would have to be compared are the black curves (marked P to highlight the virtual impact point that should be chosen had the fish immediately generated to the untrained conditions). We have rewritten the text and the labels in the Figure (now Figure 5) to illustrate the predictions and to name them in more helpful ways and so that they can't be confused with panel labels. At any rate, what needs to be compared, to check the idea, are the black curves, and these are not statistically different between both heights (p=0.525, Mann-Whitney). Interestingly, none of the black curves from all panels (D-G) differ (p>0.3).

      Line 559: if we are speaking here about luminance contrast, it should read 'Michelson Contrast' rather than 'Michelsen Contrast'.

      Absolutely, thanks!

      References

      (1) Chittka, L., Skorupski, P. & Raine, N. E. Speed-accuracy tradeoffs in animal decision making. Trends Ecol Evol 24, 400-407, doi:10.1016/j.tree.2009.02.010 (2009).

      An excellent paper that helps to stress our main question

    1. Reviewer #1 (Public review):

      In this study the authors aim to understand why decision formation during behavioural tasks is distributed across multiple brain areas. They hypothesize that multiple areas are used in order to implement an information bottleneck (IB). Using neural activity recorded from monkey DLPFC and PMd performing a 2-AFC task, they show that DLPFC represents various task variables (decision, color, target configuration), while downstream PMd primarily represents decision information. Since decision information is the only information needed to make a decision, the authors suggest that PMd has a minimal sufficient representation (as expected from an IB). They then train 3-area RNNs on the same task, and show that activity in the first and third areas resemble the neural representations of DLPFC and PMd, respectively. In order to propose a mechanism, they analyse the RNN and find that area 3 ends up with primarily decision information because feedforward connections between areas primarily propagate decision information.

      Overall, the paper reads well and the data analysis and RNN modeling are well done and mostly correct. I agree with the authors that PMd has less information than DLPFC, meaning that some of the target and color information is attenuated. I also agree that this also happens in their multi-area RNN.

      However, I find the use of the IB principle here muddles the water rather than clarifying anything. The key problem is that the authors evoke the information bottleneck in a mostly intuitive sense, but they do not actually use it (say, in their modelling). Rather, the IB is simply used to motivate why information will be or should be lost. Since the IB is a generic compressor, however, it does not make any statements about how a particular compression should be distributed or computed across brain areas.

      If I ignore the reference to the information bottleneck, I still see a more mechanistic study that proposes a neural mechanism of how decisions are formed, in the tradition of RNN-modelling of neural activity as in Mante et al 2013. Seen through this more limited sense, the present study succeeds at pointing out a good model-data match.

      Major points

      (1) The IB is a formal, information-theoretic method to identify relevant information. However, in the paper, reference to the information bottleneck method (IB) is only used to motivate why (task-irrelevant) information should be lost in higher areas. The IB principle itself is actually never used. The RNNs are fitted using standard techniques, without reference to the IB. Without a formal link, I think the authors should describe their findings using words (e.g., task-irrelevant information is lost), rather than stating this as evidence for an information-theoretic principle.

      (2) The advantage of employing a formal theory is that all assumptions have to be clarified. Since the authors only evoke the IB, but never employ it, they refrain from clarifying some of their assumptions. That is what creates unnecessary confusion.

      For instance, the authors cite the following predictions of the IB principle: "(1) There exists a downstream area of cortex that has a minimal and sufficient representation to perform a task ... (2) there exists an upstream area of cortex that has more task information than the minimal sufficient area" - However, since the information bottleneck method is a generic compressor, it does not make any predictions about areas (or neurons). For a given sensory input p(x), a given task output p(y|x), and a given information loss, the IB generates exactly one optimal representation. In other words, the predictions made by the authors relie on other assumptions (e.g. feedforward processing, hierarchy, etc.) and these are not clearly stated.

      (3) A corrollary to this problem is that the authors do not formally define task-irrelevant information. It seems the authors simply use the choice or decision as the thing that needs to be computed, and identify all other information as task-irrelevant. That's at least what I glean from the RNN model. However, I find that highly confusing because it suggests the conclusion that color information or target information are task-irrelevant. Surely, that cannot be true, since the decision is based on these quantities!

      (4) If we define the output as the only task-relevant information, then any representation that is a pure motor representation would qualify as a minimal sufficient representation to carry out the correct actions. However, it is well-known that sensory information is lost in motor areas. It is not clear to me what exactly we gain by calling motor representations "minimal sufficient representations."

      In summary, I think the authors should refrain from evoking the IB - which is a formal, mathematical principle - unless they actually use it formally as well.

    1. Author response:

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

      Reviewer #1 (Public review):

      Summary:

      In this manuscript, Pakula et al. explore the impact of reactive oxygen species (ROS) on neonatal cerebellar regeneration, providing evidence that ROS activates regeneration through Nestin-expressing progenitors (NEPs). Using scRNA-seq analysis of FACS-isolated NEPs, the authors characterize injury-induced changes, including an enrichment in ROS metabolic processes within the cerebellar microenvironment. Biochemical analyses confirm a rapid increase in ROS levels following irradiation and forced catalase expression, which reduces ROS levels, and impairs external granule layer (EGL) replenishment post-injury.

      Strengths:

      Overall, the study robustly supports its main conclusion and provides valuable insights into ROS as a regenerative signal in the neonatal cerebellum.

      Comments on revisions:

      The authors have addressed most of the previous comments. However, they should clarify the following response:

      *"For reasons we have not explored, the phenotype is most prominent in these lobules, that is why they were originally chosen. We edited the following sentence (lines 578-579):

      First, we analyzed the replenishment of the EGL by BgL-NEPs in vermis lobules 3-5, since our previous work showed that these lobules have a prominent defect."*

      It has been reported that the anterior part of the cerebellum may have a lower regenerative capacity compared to the posterior lobe. To avoid potential ambiguity, the authors should clarify that "the phenotype" and "prominent defect" refer to more severe EGL depletion at an earlier stage after IR rather than a poorer regenerative outcome. Additionally, they should provide a reference to support their statement or indicate if it is based on unpublished observations.

      Our comment does not refer to a more severe EGL depletion at an earlier stage. There is instead poorer regeneration of the anterior region. The irradiation approach used provides consistent cell killing of GCPs across the cerebellum. This can be seen in Fig. 1c, e, g, i in our previous publication: Wojcinski, et al. (2017) Cerebellar granule cell replenishment post-injury by adaptive reprogramming of Nestin+ progenitors. Nature Neuroscience, 20:1361-1370). Also, Fig 2e, g, k, m in the paper shows that by P5 and P8, posterior lobule 8 recovers better than anterior lobules 1-5.

      Reviewer #2 (Public review):

      Summary:

      The authors have previously shown that the mouse neonatal cerebellum can regenerate damage to granule cell progenitors in the external granular layer, through reprogramming of gliogenic nestin-expressing progenitors (NEPs). The mechanisms of this reprogramming remain largely unknown. Here the authors used scRNAseq and ATACseq of purified neonatal NEPs from P1-P5 and showed that ROS signatures were transiently upregulated in gliogenic NEPs ve neurogenic NEPs 24 hours post injury (P2). To assess the role of ROS, mice transgenic for global catalase activity were assessed to reduce ROS. Inhibition of ROS significantly decreased gliogenic NEP reprogramming and diminished cerebellar growth post-injury. Further, inhibition of microglia across this same time period prevented one of the first steps of repair - the migration of NEPs into the external granule layer. This work is the first demonstration that the tissue microenvironment of the damaged neonatal cerebellum is a major regulator of neonatal cerebellar regeneration. Increased ROS is seen in other CNS damage models, including adults, thus there may be some shared mechanisms across age and regions, although interestingly neonatal cerebellar astrocytes do not upregulate GFAP as seen in adult CNS damage models. Another intriguing finding is that global inhibition of ROS did not alter normal cerebellar development.

      Strengths:

      This paper presents a beautiful example of using single cell data to generate biologically relevant, testable hypotheses of mechanisms driving important biological processes. The scRNAseq and ATACseq analyses are rigorously conducted and conclusive. Data is very clearly presented and easily interpreted supporting the hypothesis next tested by reduce ROS in irradiated brains.

      Analysis of whole tissue and FAC sorted NEPS in transgenic mice where human catalase was globally expressed in mitochondria were rigorously controlled and conclusively show that ROS upregulation was indeed decreased post injury and very clearly the regenerative response was inhibited. The authors are to be commended on the very careful analyses which are very well presented and again, easy to follow with all appropriate data shown to support their conclusions.

      Weaknesses:

      The authors also present data to show that microglia are required for an early step of mobilizing gliogenic NEPs into the damaged EGL. While the data that PLX5622 administration from P0-P5 or even P0-P8 clearly shows that there is an immediate reduction of NEPs mobilized to the damaged EGL, there is no subsequent reduction of cerebellar growth such that by P30, the treated and untreated irradiated cerebella are equivalent in size. There is speculation in the discussion about why this might be the case. Additional experiments and tools are required to assess mechanisms. Regardless, the data still implicate microglia in the neonatal regenerative response, and this finding remains an important advance.

      As stated previously, the suggested follow up experiments while relevant are extensive and considered beyond the scope of the current paper.


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

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      In this manuscript, Pakula et al. explore the impact of reactive oxygen species (ROS) on neonatal cerebellar regeneration, providing evidence that ROS activates regeneration through Nestin-expressing progenitors (NEPs). Using scRNA-seq analysis of FACS-isolated NEPs, the authors characterize injury-induced changes, including an enrichment in ROS metabolic processes within the cerebellar microenvironment. Biochemical analyses confirm a rapid increase in ROS levels following irradiation, and forced catalase expression, which reduces ROS levels, and impairs external granule layer (EGL) replenishment post-injury.

      Strengths:

      Overall, the study robustly supports its main conclusion and provides valuable insights into ROS as a regenerative signal in the neonatal cerebellum.

      Weaknesses:

      (1) The diversity of cell types recovered from scRNA-seq libraries of sorted Nes-CFP cells is unexpected, especially the inclusion of minor types such as microglia, meninges, and ependymal cells. The authors should validate whether Nes and CFP mRNAs are enriched in the sorted cells; if not, they should discuss the potential pitfalls in sampling bias or artifacts that may have affected the dataset, impacting interpretation.

      In our previous work, we thoroughly assessed the transgene using RNA in situ hybridization for Cfp, immunofluorescent analysis for CFP and scRNA-seq analysis for Cfp transcripts (Bayin et al., Science Adv. 2021, Fig. S1-2)(1), and characterized the diversity within the NEP populations of the cerebellum. Our present scRNA-seq data also confirms that Nes transcripts are expressed in all the NEP subtypes. A feature plot for Nes expression has been added to the revised manuscript (Fig 1E), as well as a sentence explaining the results. Of note, since this data was generated from FACS-isolated CFP+ cells, the perdurance of the protein allows for the detection of immediate progeny of Nes-expressing cells, even in cells where Nes is not expressed once cells are differentiated. Finally, oligodendrocyte progenitors, perivascular cells, some rare microglia and ependymal cells have been demonstrated to express Nes in the central nervous system; therefore, detecting small groups of these cells is expected (2-4). We have added the following sentence (lines 391-394):

      “Detection of Nes mRNA confirmed that the transgene reflects endogenous Nes expression in progenitors of many lineages, and also that the perdurance of CFP protein in immediate progeny of Nes-expressing cells allowed the isolation of these cells by FACS (Figure 1E)”.

      (2) The authors should de-emphasize that ROS signaling and related gene upregulation exclusively in gliogenic NEPs. Genes such as Cdkn1a, Phlda3, Ass1, and Bax are identified as differentially expressed in neurogenic NEPs and granule cell progenitors (GCPs), with Ass1 absent in GCPs. According to Table S4, gene ontology (GO) terms related to ROS metabolic processes are also enriched in gliogenic NEPs, neurogenic NEPs, and GCPs.

      As the reviewer requested, we have de-emphasized that ROS signaling is preferentially upregulated in gliogenic NEPs, since we agree with the reviewer that there is some evidence for similar transcriptional signatures in neurogenic NEPs and GCPs. We added the following (lines 429-531):

      “Some of the DNA damage and apoptosis related genes that were upregulated in IR gliogenic-NEPs (Cdkn1a, Phlda3, Bax) were also upregulated in the IR neurogenic-NEPs and GCPs at P2 (Supplementary Figure 2B-E).”

      And we edited the last few sentences of the section to state (lines 453-459):

      “Interestingly, we did not observe significant enrichment for GO terms associated with cellular stress response in the GCPs that survived the irradiation compared to controls, despite significant enrichment for ROS signaling related GO-terms (Table S4). Collectively, these results indicate that injury induces significant and overlapping transcriptional changes in NEPs and GCPs. The gliogenic- and neurogenic-NEP subtypes transiently upregulate stress response genes upon GCP death, and an overall increase in ROS signaling is observed in the injured cerebella.”

      (3) The authors need to justify the selection of only the anterior lobe for EGL replenishment and microglia quantification.

      We thank the reviewers for asking for this clarification. Our previous publications on regeneration of the EGL by NEPs have all involved quantification of these lobules, thus we think it is important to stay with the same lobules. For reasons we have not explored, the phenotype is most prominent in these lobules, that is why they were originally chosen. We edited the following sentence (lines 578-579):

      “First, we analyzed the replenishment of the EGL by BgL-NEPs in vermis lobules 3-5, since our previous work showed that these lobules have a prominent defect.”

      (4) Figure 1K: The figure presents linkages between genes and GO terms as a network but does not depict a gene network. The terminology should be corrected accordingly.

      We have corrected the terminology and added the following (lines 487-489):

      “Finally, linkages between the genes in differentially open regions identified by ATAC-seq and the associated GO-terms revealed an active transcriptional network involved in regulating cell death and apoptosis (Figure 1K).”

      (5) Figure 1H and S2: The x-axis appears to display raw p-values rather than log10(p.value) as indicated. The x-axis should ideally show -log10(p.adjust), beginning at zero. The current format may misleadingly suggest that the ROS GO term has the lowest p-values.

      Apologies for the mistake. The data represents raw p-values and the x-axis has been corrected.

      (6) Genes such as Ppara, Egln3, Foxo3, Jun, and Nos1ap were identified by bulk ATAC-seq based on proximity to peaks, not by scRNA-seq. Without additional expression data, caution is needed when presenting these genes as direct evidence of ROS involvement in NEPs.

      We modified the text to discuss the discrepancies between the analyses. While some of this could be due to the lower detection limits in the scRNA-seq, it also highlights that chromatin accessibility is not a direct readout for expression levels and further analysis is needed. Nevertheless, both scRNA-seq and ATAC-seq have identified similar mechanisms, and our mutant analysis confirmed our hypothesis that an increase in ROS levels underlies repair, further increasing the confidence in our analyses. Further investigation is needed to understand the downstream mechanisms. We added the following sentence (lines 478-481):

      “However, not all genes in the accessible areas were differentially expressed in the scRNA-seq data. While some of this could be due to the detection limits of scRNA-seq, further analysis is required to assess the mechanisms of how the differentially accessible chromatin affects transcription.”

      (7) The authors should annotate cell identities for the different clusters in Table S2.

      All cell types have been annotated in Table S2.

      (8) Reiterative clustering analysis reveals distinct subpopulations among gliogenic and neurogenic NEPs. Could the authors clarify the identities of these subclusters? Can we distinguish the gliogenic NEPs in the Bergmann glia layer from those in the white matter?

      Thank you for this clarification. As shown in our previous studies, we can not distinguish between the gliogenic NEPs in the Bergmann glia layer and the white matter based on scRNA-seq, but expression of the Bergmann glia marker Gdf10 suggests that a large proportion of the cells in the Hopx+ clusters are in the Bergmann glia layer. The distinction within the major subpopulations that we characterized (Hopx-, Ascl1-expressing NEPs and GCPs) are driven by their proliferative/maturation status as we previously observed. We have included a detailed annotation of all the clusters in Table S2, as requested and a UMAP for mKi57 expression in Fig 1E. We have clarified this in the following sentence (lines 383-385):

      “These groups of cells were further subdivided into molecularly distinct clusters based on marker genes and their cell cycle profiles or developmental stages (Figure 1D, Table S2).”

      (9) In the Methods section, the authors mention filtering out genes with fewer than 10 counts. They should specify if these genes were used as background for enrichment analysis. Background gene selection is critical, as it influences the functional enrichment of gene sets in the list.

      As requested, the approach used has been added to the Methods section of the revised paper. Briefly, the background genes used by the goseq function are the same genes used for the probability weight function (nullp). The mm8 genome annotation was used in the nullp function, and all annotated genes were used as background genes to compute GO term enrichment. The following was added (lines 307-308):

      “The background genes used to compute the GO term enrichment includes all genes with gene symbol annotations within mm8.”

      (10) Figure S1C: The authors could consider using bar plots to better illustrate cell composition differences across conditions and replicates.

      As suggested, we have included bar plots in Fig. S1D-F.

      (11) Figures 4-6: It remains unclear how the white matter microglia contribute to the recruitment of BgL-NEPs to the EGL, as the mCAT-mediated microglia loss data are all confined to the white matter.

      We have thought about the question and had initially quantified the microglia in the white matter and the rest of the lobules (excluding the EGL) separately. However, there are very few microglia outside the white matter in each section, thus it is not possible to obtain reliable statistical data on such a small population. We therefore did not include the cells in the analysis. We have added this point in the main text (line 548).

      “As a possible explanation for how white matter microglia could influence NEP behaviors, given the small size of the lobules and how the cytoarchitecture is disrupted after injury, we think it is possible that secreted factors from the white matter microglia could reach the BgL NEPs. Alternatively, there could be a relay system through an intermediate cell type closer to the microglia.” We have added these ideas to the Discussion of the revised paper (lines 735-738).

      Reviewer #2 (Public review):

      Summary:

      The authors have previously shown that the mouse neonatal cerebellum can regenerate damage to granule cell progenitors in the external granular layer, through reprogramming of gliogenic nestin-expressing progenitors (NEPs). The mechanisms of this reprogramming remain largely unknown. Here the authors used scRNAseq and ATACseq of purified neonatal NEPs from P1-P5 and showed that ROS signatures were transiently upregulated in gliogenic NEPs ve neurogenic NEPs 24 hours post injury (P2). To assess the role of ROS, mice transgenic for global catalase activity were assessed to reduce ROS. Inhibition of ROS significantly decreased gliogenic NEP reprogramming and diminished cerebellar growth post-injury. Further, inhibition of microglia across this same time period prevented one of the first steps of repair - the migration of NEPs into the external granule layer. This work is the first demonstration that the tissue microenvironment of the damaged neonatal cerebellum is a major regulator of neonatal cerebellar regeneration. Increased ROS is seen in other CNS damage models including adults, thus there may be some shared mechanisms across age and regions, although interestingly neonatal cerebellar astrocytes do not upregulate GFAP as seen in adult CNS damage models. Another intriguing finding is that global inhibition of ROS did not alter normal cerebellar development.

      Strengths:

      This paper presents a beautiful example of using single cell data to generate biologically relevant, testable hypotheses of mechanisms driving important biological processes. The scRNAseq and ATACseq analyses are rigorously conducted and conclusive. Data is very clearly presented and easily interpreted supporting the hypothesis next tested by reduce ROS in irradiated brains.

      Analysis of whole tissue and FAC sorted NEPS in transgenic mice where human catalase was globally expressed in mitochondria were rigorously controlled and conclusively show that ROS upregulation was indeed decreased post injury and very clearly the regenerative response was inhibited. The authors are to be commended on the very careful analyses which are very well presented and again, easy to follow with all appropriate data shown to support their conclusions.

      Weaknesses:

      The authors also present data to show that microglia are required for an early step of mobilizing gliogenic NEPs into the damaged EGL. While the data that PLX5622 administration from P0-P5 or even P0-P8 clearly shows that there is an immediate reduction of NEPs mobilized to the damaged EGL, there is no subsequent reduction of cerebellar growth such that by P30, the treated and untreated irradiated cerebella are equivalent in size. There is speculation in the discussion about why this might be the case, but there is no explanation for why further, longer treatment was not attempted nor was there any additional analyses of other regenerative steps in the treated animals. The data still implicate microglia in the neonatal regenerative response, but how remains uncertain.

      Recommendations for the authors:

      Reviewer #2 (Recommendations for the authors):

      This is an exemplary manuscript.

      The methods and data are very well described and presented.

      I actually have very little to ask the authors except for an explanation of why PLX treatment was discontinued after P5 or P8 and what other steps of NEP reprogramming were assessed in these animals? Was NEP expansion still decreased at P8 even in the presence of PLX at this stage? Also - was there any analysis attempted combining mCAT and PLX?

      We agree with the reviewer that a follow up study that goes into a deeper analysis of the role of microglia in GCP regeneration and any interaction with ROS signaling would interesting. However, it would require a set of tools that we do not currently have. We did not have enough PLX5622 to perform addition experiments or extend the length of treatment. Plexxikon informed us in 2021 that they were no longer manufacturing PLX5622 because they were focusing on new analogs for in vivo use, and thus we had to use what we had left over from a completed preclinical cancer study. We nevertheless think it is important to publish our preliminary results to spark further experiments by other groups.

      References

      (1) Bayin N. S. Mizrak D., Stephen N. D., Lao Z., Sims P. A., Joyner A. L. Injury induced ASCL1 expression orchestrates a transitory cell state required for repair of the neonatal cerebellum. Sci Adv. 2021;7(50):eabj1598.

      (2) Cawsey T, Duflou J, Weickert CS, Gorrie CA. Nestin-Positive Ependymal Cells Are Increased in the Human Spinal Cord after Traumatic Central Nervous System Injury. J Neurotrauma. 2015;32(18):1393-402.

      (3) Gallo V, Armstrong RC. Developmental and growth factor-induced regulation of nestin in oligodendrocyte lineage cells. The Journal of neuroscience : the official journal of the Society for Neuroscience. 1995;15(1 Pt 1):394-406.

      (4) Huang Y, Xu Z, Xiong S, Sun F, Qin G, Hu G, et al. Repopulated microglia are solely derived from the proliferation of residual microglia after acute depletion. Nat Neurosci. 2018;21(4):530-40.

    1. class ResNetLayer4(torch.nn.Module):

      这里 ResNetLayer4 模块通过在 ResNet-152 的第四个大块(layer4)上注册一个 forward hook,实现“截断式”特征提取:

      1. 初始化 ResNet

        • self.r_model = resnet.resnet152(pretrained=True):加载预训练的 ResNet-152

        • self.r_model.eval():切换到推理模式,禁用 dropout/BatchNorm 的训练行为

        • self.r_model.to(device):把模型搬到指定设备(CPU/GPU)上

      2. 缓冲输出

        • self.buffer = {} 用于存储钩子捕获的中间特征,以设备(output.device)为 key。

        • threading.Lock() 保证多线程/多卡场景下写入 buffer 的线程安全。

      3. 注册 Hook

        python def save_output(module, input, output): with lock: self.buffer[output.device] = output self.r_model.layer4.register_forward_hook(save_output)

        • 每当你对 r_model 调用一次 forward(x),ResNet 在执行到 layer4 这一大层的前向输出时,就会触发 save_output,把这一层的输出张量存进 self.buffer
      4. 截断执行

        • 注意这段代码并没有手动抛出异常来提前终止整个网络的前向传播,而是简单地“跑完”了 ResNet 的所有层。

        • 如果想更早停止,可以在 hook 里抛一个自定义异常,然后在 forward 方法里捕获并忽略,以节省多余计算。

      5. forward(x)

        python self.r_model(x) return self.buffer[x.device]

        • 调用 self.r_model(x),内部 hook 会把 layer4 的输出保存在 buffer

        • 然后直接从 buffer 里取出,不用关心后续的 layer5 或分类头,得到形状 (batch_size, 2048, h, w) 的特征图。


      self.buffer[x.device] 就是你想截取的 ResNet-152 的第四大层(layer4)对输入 x 做前向计算后产生的中间特征张量。具体来说:

      • 当你执行 self.r_model(x) 时,ResNet 会从第一层一路算到最后。在它走到 layer4(第四个残差大块)完成前向输出时,你注册的钩子函数 save_output 会被触发,把那一层的输出 output 存到 self.buffer[output.device]

      • output 的形状通常是 (batch_size, 2048, H', W'),其中

        • batch_size 与输入 x 的第 0 维相同
        • <u>通道数 2048 来自 ResNet-152 在第四层的输出通道数</u>
        • H', W' 是经过前面多次下采样后的空间尺寸(如果输入图像是 224×224,则通常是 7×7)
      • forward(x) 里,你调用 self.r_model(x) 完成一次完整的前向过程后,直接通过 return self.buffer[x.device] 拿到刚才存的那份中间特征。x.device 只是用来从可能的多个设备缓存里取出对应 GPU(或 CPU)上的结果。

      因此,最终返回的就是一个 Tensor,代表输入 x 在 ResNet-152 的 layer4 处的激活特征图,方便你后续在 VQA 模型中接着做归一化、注意力、融合、分类等操作。

    2. class VQA_Resnet_Model

      VQA_Resnet_Model 中: - 继承并初始化父类

       ```python
       super().__init__(embedding_tokens)
       ```
      
       这一行把 `embedding_tokens`(词表大小)交给父类 `Net` 去创建文本嵌入、注意力模块和分类头,子类无需重复这些逻辑。
      
      • ResNetLayer4 会在内部用 forward‐hook “截取”预训练 ResNet-152 的第 4 大 block 的输出。

      forward

      • 文本处理

      python q = self.text(q, list(q_len.data))

      把问题的词索引 q 和它们的长度 q_len 输入到父类定义的文本编码器,得到一个固定维度的语义向量 q

      • 图像特征提取 v = self.resnet_layer4(v) 得到每张图像经过 ResNet-152 前 4 个大块后的空间特征图,得到形状为 (batch_size, 2048, H′, W′) 的空间特征图。

      • L2 归一化

      python v = v / (v.norm(p=2, dim=1, keepdim=True).expand_as(v) + 1e-8)

      对每个通道特征向量做单位长度归一化,稳定后续注意力计算。

      • 注意力机制 & 特征融合

      python a = self.attention(v, q) v = apply_attention(v, a)

      用文本向量 q 引导图像特征 v 上的空间注意力 a,再把注意力权重应用到 v 上,得到一个融合后的图像语义向量。

      • 拼接 & 分类

      python combined = torch.cat([v, q], dim=1) answer = self.classifier(combined)

      把图像和文本的融合特征在通道维度上拼起来,送入父类的分类头 self.classifier(一系列全连接层+激活)得到最终的答案 logits。


      这样做的好处是“零改动”地复用了 torchvision 的预训练模型,仅通过 hook 快速拿到其中间层特征,而无需拷贝或重写 ResNet 模型定义。

    3. saved_state

      这段代码主要是从之前保存的模型检查点中恢复词汇表,并把索引映射反向构造成便于查找的列表:

      1. saved_state = torch.load(..., map_location=device) 载入了一个字典结构的检查点,其中至少包含了模型权重和一个名为 vocab 的子字典。map_location=device 保证无论原来是在哪个设备上保存,都能映射到当前的 device(CPU 或 GPU)。

      2. vocab = saved_state['vocab'] 取出检查点里的词汇表。通常这个 vocab 会是一个包含多个子映射(比如对问题词、答案词、甚至对图像区域标签等)的字典。

      3. token_to_index = vocab['question']vocab 里读取 “问题(question)” 里面的到索引映射。这里 token_to_index 是一个 {word: idx} 的字典,用于把输入问题的每个词转换成模型能处理的整数索引。

      4. answer_to_index = vocab['answer'] 同理,读取 “答案(answer)” 的词到索引映射。常见于 VQA(Visual Question Answering)等任务,模型最后要预测的是这个映射集合里的某一个或若干个答案类别。

      5. num_tokens = len(token_to_index) + 1 计算问题词表的大小并加 1,这里通常是为了给可能的 paddingunknown 预留一个额外索引位置。

      6. 构造 answer_words 列表:

        python answer_words = ['unk'] * len(answer_to_index) for w, idx in answer_to_index.items(): answer_words[idx] = w

        • 先创建一个长度等于答案词表大小的列表、初始全部填 'unk'
        • 再遍历 answer_to_index,把每个答案词 w 放到它对应的 idx 位置。 这样,通过 answer_words[idx] 就能快速地把模型输出的类别索引映射回对应的自然语言答案。

      最终,你得到了:

      • 一个能把输入问题词转成索引的字典 token_to_index
      • 一个能把输出预测索引转回字符串答案的列表 answer_words
      • 以及问题词表的大小 num_tokens,可用于后续构建词嵌入层或定义嵌入矩阵维度。
    1. Author response:

      The following is the authors’ response to the original reviews

      Public Reviews:

      Reviewer #1 (Public reviews):

      (1) A cartoon paradigm of the HFD treatment window would be a helpful addition to Figure 1. Relatedly, the authors might consider qualifying MHFD as 'lactational MHFD.' Readers might miss the fact that the exposure window starts at birth.

      This is a good suggestion. The MHFD-L model has been used previously (e.g. Vogt et al. 2014). We have included a cartoon of the MHFD-L model and the PLX treatments to Figure 4, which we feel helps the readers and thank the reviewer for the suggestion.

      (2) More details on the modeling pipeline are needed either in Figure 1 or text. Of the ~50 microglia that were counted (based on Figure 1J), were all 50 quantified for the morphological assessments? Were equal numbers used for the control and MHFD groups? Were the 3D models adjusted manually for accuracy? How much background was detected by IMARIS that was discarded? Was the user blind to the treatment group while using the pipeline? Were the microglia clustered or equally spread across the PVN?

      In response to this suggestion, we have expanded the description of the image analysis routine in the methods. The analysis focused on detailed changes in microglial morphology as opposed to overall changes in microglia throughout the PVH as a whole. Accordingly, we applied anatomically matched ROIs to the PVH for the measurements. As described in the methods, the Imaris Filaments tool was used to visualize microglia fully contained within a tissue section and a mask derived from the 3D model for these cells was used to isolate them for further analysis, thereby separating these cells from interstitial labeling corresponding to parts of cell processes or other labeling not associated with selected cells. There was no formal “background subtraction.” This was an error in the previous version of the manuscript and we have revised the methods to reflect the process actually used. The images were segmented (to enhance signal to noise for 3D rendering), and then a Gaussian filter was applied to improve edge detection, which facilitates the morphological measurements.

      (3) Suggest toning back some of the language. For example: "...consistent with enhanced activity and surveillance of their immediate microenvironment" (Line 195) could be "...perhaps consistent with...". Likewise, "profound" (Lines 194, 377) might be an overstatement.

      Revisions have been made to both the Introduction and Discussion to modulate our representation of this controversial issue.

      (4) Representative images for AgRP+ cells (quantified in Figure 2J) are missing. Why not a co-label of Iba1+/AgRP+ as per Figure 1, 3? Also, what was quantified in Figure 2J - soma? Total immunoreactivity?

      Because the density of AgRP labeling does not change in the ARH we omitted the red channel image (AgRP labeling) to highlight the similarity of the microglial morphology. To address the reviewer’s concerns, in the revised figure we have reconstituted the figure with both the green (microglial) and red (AgRP) channels depicted.

      Figure 2J displays the numbers of AgRP neurons counted in the ARH in selected R01s through the ARH. The Methods section has been revised to include the visualization procedure used for the cell counts.

      (5) For the PLX experiment:

      a) "...we depleted microglia during the lactation period" (Line 234). This statement suggests microglia decreased from the first injection at P4 and throughout lactation, which is inaccurate. PLX5622 effects take time, upwards of a week. Thus, if PLX5622 injections started at P4, it could be P11 before the decrease in microglia numbers is stable. Moreover, by the time microglia are entirely knocked down, the pups might be supplementing some chow for milk, making it unclear how much PLX5622 they were receiving from the dam, which could also impact the rate at which microglia repopulation commences in the fetal brain. Quantifying microglia across the P4-P21 treatment window would be helpful, especially at P16, since the PVN AgRP microglia phenotypes were demonstrated and roughly when pups might start eating some chow. b) I am surprised that ~70% of the microglia are present at P21. Does this number reflect that microglia are returning as the pups no longer receive PLX5622 from milk from the dam? Does it reflect the poor elimination of microglia in the first place?

      This is an important point and have revised the first sentence in section 2.3 to clarify the PLX treatment logic and added a cartoon to Fig. 4 to show the treatment timeline. The PLX5622 was not administered to the dams but daily to the pups. We also agree with the interpretation that PLX5622 depleted numbers of microglia, as supported by the microglial cell counts, rather than effected a complete elimination and have made revisions to clarify this distinction. Although mice were weighed at weaning, cellular measurements were only made in mice perfused at P55.

      (6) Was microglia morphology examined for all microglia across the PVN? It is possible that a focus on PVNmpd microglia would reveal a stronger phenotype? In Figure 4H, J, AgRP+ terminals are counted in PVN subregions - PVNmpd and PVNpml, with PVNmpd showing a decrease of ~300 AgRP+ terminals in MHFD/Veh (rescued in MHFD/PLX5622). In Figure 1K, AgRP+ terminals across what appears to be the entire PVN decrease by ~300, suggesting that PVNmpd is driving this phenotype. If true, then do microglia within the PVNmpd display this morphology phenotype?

      We have revised the description of the analysis procedures to clarify these points. All measurements were made in user defined, matched regions of interest according to morphological features of the PVH. No measurements were made that included the entire PVH and we revised the Methods section to improve clarity.

      (7) What chow did the pups receive as they started to consume solid food? Is this only a MHFD challenge, or could the pups be consuming HFD chow that fell into the cage?

      The pups were weaned onto the same normal chow diet that the dams received prior to MHFD-L treatment. The cages were inspected daily and minimal HFD spillage was observed, although we cannot rule out with certainty any contribution of the pups directly consuming the HFD. We have edited Methods section 5.2 for clarity.

      (8) Figure 5: Does internalized AgRP+ co-localize with CD68+ lysosomes? How was 'internalized' determined?

      This important point has been clarified by revisions to the Methods section.

      (9) Different sample sizes are used across experiments (e.g., Figure 4 NCD n=5, MHFD n=4). Does this impact statistical significance?

      Sample size does impact power of ANOVA with larger samples reducing the chance of errors. ANOVA is generally robust in the face of moderate departures from the assumption of equal sample sizes and equal variance such as we experienced in the PLX5622 experiment. Here we used t-tests to detect differences in a single variable between two groups and two-way ANOVA to compare treatment by diet and treatment changes in the PLX5622 studies. Additional detail has been added to the Methods section to clarify this point.

      Reviewer #2 (Public reviews):

      (1) Under chow-fed conditions, there is a decrease in the number of microglia in the PVH and ARH between P16 and P30, accompanied by an increase in complexity/volume. With the exception of PVH microglia at P16, this maturation process is not affected by MHFD. This "transient" increase in microglial complexity could also reflect premature maturation of the circuit.

      This is an interesting possibility that requires future investigation (see response to Recommended Suggestions, above).

      (2) The key experiment in this paper, the ablation of microglia, was presumably designed to prevent microglial expansion/activation in the PVH of MHFD pups. However, it also likely accelerates and exaggerates the decrease in cell number during normal development regardless of maternal diet. Efforts to interpret these findings are further complicated because microglial and AgRP neuronal phenotypes were not assessed at earlier time points when the circuit is most sensitive to maternal influences.

      We agree that evaluations of microglia and hypothalamic circuits at many more time points would indeed be informative (see comments above).

      (3) Microglial loss was induced broadly in the forebrain. Enhanced AgRP outgrowth to the PVH could be caused by actions elsewhere, such as direct effects on AgRP neurons in the ARH or secondary effects of changes in growth rates.

      A local effect of microglia in the ARH that affects growth of AgRP axons remains a distinct possibility that deserves a targeted examination (see response to Recommended Suggestions, above).

      (4) Prior publications from the authors and other groups support the idea that the density of AgRP projections to the PVH is primarily driven by factors regulating outgrowth and not pruning. The failure to observe increased engulfment of AgRP fibers by PVH microglia is therefore not surprising. The possibility that synaptic connectivity is modulated by microglia was not explored.

      Synaptic pruning and regulation of axon targeting are not mutually exclusive processes and microglia may participate in both. Here we evaluated innervation of the PVH, which is sensitive to MHFD-L exposure, and engulfment of AgRP terminals by microglia, which does appear to be altered by MHFD-L. Given previous observations of terminal engulfment by microglia in other brain regions in response to environmental changes (e.g. prolonged stress) it is not unreasonable to expect this outcome in the offspring of MHFD-L dams.  In future work it will be important to profile multiple cell types in the PVH for microglial dependent and MHFDL-sensitive changes in targeting of AgRP axons. Equally important is a full characterization of postsynaptic changes in PVH neurons.

      Reviewer #3 (Public reviews):

      There was no attempt to interrogate microglia in different parts of the hypothalamus functionally. Morphology alone does not reflect a potential for significant signaling alterations that may occur within and between these and other cell types.

      The authors should discuss the limitations of their approach and findings and propose future directions to address them.

      We agree that evaluations of microglia and hypothalamic circuits at many more time points that include analyses of multiple regions would indeed be informative. We have added statements to the manuscript that address the limitations of our experimental approach and suggest future studies that will extend understanding of underlying mechanisms beyond those investigated here.

      Recommendations for the authors:

      Reviewing Editors Comments:

      (1) The Abstract is 405 words and should be shortened to less than 200 words.  

      The abstract has been edited to 200 words.

      (2) The authors might consider raising the question in the Introduction of whether reduced AgRP innervation of the PVN in MHFD-treated mice is due to decreased axonal growth, enhanced microglial-mediated pruning, or a combination of both. The potential effects on axonal growth should be given more consideration.

      This is an important point that we agree deserves additional consideration in the manuscript. Our past work has focused on leptin’s ability to influence axonal targeting of PVH neurons by AgRP and PPG neurons through a cell-autonomous mechanism and our conclusion is that leptin primarily induces axon growth. Because in this study our design did not focus on changes in axon growth over time but on regional changes in microglia and their interactions with AgRP terminals we did not want to divert attention from our logic in the introduction by highlighting multiple mechanisms. However, we have added a brief mention in the Introduction and have expanded consideration of axonal growth effects to the Discussion. Distinguishing between microglia’s role in synaptic density or axon targeting in this pathway is an important goal of future work.

      (3) Line 37, a high-fat diet should be defined here as HFD and used consistently thereafter. Note that "high-fat-diet exposure" requires two hyphens.

      The suggested revisions have been made throughout the manuscript.

      (4) Line 38 and elsewhere, MHFD does not adequately describe the treatment being limited to the lactation period, perhaps MLHFD would be better or just LHFD (because the pups can't lactate).

      The suggested revisions have been made throughout the manuscript, and we have used MHFD-L to describe maternal consumption of a high-fat diet that is restricted to the lactation period.

      (5) Line 110, leptin-deficient mice (add hyphen).

      (6) Line 183, NCD should be defined.

      The suggested revisions have been made throughout the manuscript.

      (7) Lines 237- 238, it is not clear what is widespread in the rostral forebrain. Is it the loss of microglia? What is the dividing point between the rostral and caudal forebrain? Were microglia depleted in the caudal forebrain too?

      We have revised this section of the manuscript to focus the description on the hypothalamus alone and specify that the reduction in microglial density is not restricted to the PVH.  

      (8) Line 245, microglial-mediated effects (add hyphen).

      (9) Line 247, vehicle-treated mice (add hyphen).

      The suggested revisions have been made throughout the manuscript.

      (10) Line 457, when referring to genes, the approved gene name should be used in italics, AgRP should be Agrp (italics).

      The suggested revision has been made throughout the manuscript.

      (11) Line 459, the name of the Syn-Tom mice in the Key Resource table, Methods, and Text should be consistent. It would be best to use the formal name of the Ai34 line of mice on the JAX website.

      The suggested revisions have been made throughout the manuscript.

      (12) Figure 1G H, and I um should have Greek micro; Fig. 1J and K, Replace # with Number. The same suggestions apply to all the other figures.

      Both the manuscript and figures have been revised in accordance with this recommendation.

      (13) Figures 4 G, H, I and J. and Figures 5 M and O. The font size is too small to see well.

      Fonts have been changed in the figures to improve visibility.

      Reviewer #1 (Recommendations for the authors):

      (1) Figures are out of order in the text. For example, Figure 1A is followed next by the results for Figure 1J instead of Figure 1B.

      We regret that the organization of figure panels makes for awkward matching for the reader as they proceed through the text. We designed the figures to facilitate comparisons between cellular responses and differences in labeling. After evaluating a reorganization, we decided to maintain the original panel configurations, but have revised the text to more closely follow the presentation of cellular features in the figures.

      (2) Figure 1B.: All images lack scale bars.

      (3) Line 433 - 'underlie' is spelled wrong.

      (4) Rosin et al should be 2019 and not 2018.

      These corrections have been implemented in the revised text and figures.

      (5) The statement that "the effects of MHFD on microglial morphology in the PVH of offspring display both temporal and regional specificity, which correspond to a decrease in the density of AgRP inputs to the PVH" (Line 196) needs clarification, as the phrase "regional specificity" has not been substantiated in this section even though it is discussed later.

      We agree with this comment and have revised section 2.1 to more closely match the data presented to this point in the manuscript.

      Reviewer #2 (Recommendations for the authors):

      (1) The claim of "spatial specificity" in the effects of MHFD on microglia is based on an increase in the complexity/volume of microglia at P16 in the PVH that was not seen in the ARH or BNST. The transient nature of the effect raises several questions: Does the effect on the PVH represent premature maturation?

      This is an interesting suggestion. However, given how little is known about microglial maturation in the hypothalamus it is difficult to address. It is indeed possible that microglia mature at different rates in each AgRP target, and that MHFD-L exposure alters the rate of maturation in some regions but not others. This will require a great deal more analysis of both microglia and ARH projections to understand fully (see below).

      (2) To support their central claim that microglia in the PVH "sculpt the density of AgRP inputs to the PVH" the authors report effects on Iba1+ cells in the PVH of chow-fed dams at P55, body weight at P21, and AgRP projections in the PVH at an unspecified age. It is hard to understand what is happening across "normal" development in chow-fed dams since the number of Iba1+ cells decreases from ~50 to ~25 between P16 and P30 (Figure 1), but then increases to >60 cells at P55 (Figure 4). Given the large fluctuations in microglial population across time, analyzing the same parameters (i.e. microglial number/morphology in the ARH and PVH, AgRP neuronal number in the ARH, and fiber density in the PVH, and body weight) across time points before, during and after the critical period in chow and MHFD conditions would be very helpful.

      The time points we evaluated were chosen to be during and after the previously determined critical period for development of AgRP projections to the PVH, which were then compared with adults (which were all P55) to assess longevity of the effects. We have incorporated revisions to improve the clarity of when measurements were assessed, and treatments implemented. Defining the cellular dynamics of microglia across time remains a major challenge for the field and will certainly be informed by future studies with additional time points, as well as by in vivo imaging studies focused on regions identified here. Although such studies are beyond the scope of the present work, their completion would advance our current understanding of how microglia respond to nutritional changes during development of feeding circuits.

      (3) As microglia are also ablated in the ARH, direct effects on AgRP neurons or indirect effects via changes in growth rates could also contribute to increased AgRP fiber density in the PVH. In support of the first possibility, postnatal microglial depletion increases the number of AgRP neurons (Sun, et al. 2023).

      We agree with the suggestion, also raised by the Reviewing Editor, which has been addressed briefly in the Introduction, and in more detail by revisions to the Discussion section.

      (4) The failure to assess alpha-MSH fibers in the same animals was a missed opportunity. They are also affected by MHFD but likely involve a distinct mechanism (Vogt, et al 2014).

      Given the paired interest in POMC neurons and AgRP neurons I understand the reviewer’s comment. We chose to focus solely on AgRP neurons because we do not currently have a way to genetically target axonal labeling exclusively to POMC neurons due to the shared precursor origin of POMC neurons and a percentage of NPY neurons in the ARH, as shown by Lori Zeltser’s laboratory. Moreover, the elegant work by Vogt et al. focused on responses of POMC neurons in the MHFD-L model. However, it certainly remains possible that microglia in the PVH interact with terminals derived from POMC neurons, as well as with terminals derived from other afferent populations of neurons.

      (5) All statistical analyses involved unpaired t-tests. Two-way ANOVAs should be used to assess the effects of age and HFD and interactions between these factors.

      We used t-tests to detect differences in a single variable between two groups and two-way ANOVA to compare treatment by diet and treatment changes in the PLX5622 studies.  Additional detail has been added to the Methods section and information added to the figure legend for Fig. 4 to clarify this point.

      Reviewer #3 (Recommendations for the authors):

      I suggest exploring the deeper characterization of the microglia in various parts of the hypothalamus in different conditions. This could include cytokine assessment or spatial transcriptomic.

      We agree that a great deal more work is needed to improve our understanding of how microglia impact hypothalamic development more broadly and to identify underlying molecular mechanisms. We are hopeful that the data presented here will motivate additional study of microglial dynamics in multiple hypothalamic regions, as well as detailed studies of cellular signaling events for factors derived from MHFD-L dams that impact neural development in the hypothalamus.

    1. Reviewer #1 (Public review):

      Summary:

      In this manuscript, the authors used a leucine/pantothenate auxotrophic strain of Mtb to screen a library of FDA-approved compounds for their antimycobacterial activity and found significant antibacterial activity of the inhibitor semapimod. In addition to alterations in pathways, including amino acid and lipid metabolism and transcriptional machinery, the authors demonstrate that semapimod treatment targets leucine uptake in Mtb. The work presents an interesting connection between nutrient uptake and cell wall composition in mycobacteria.

      Strengths:

      (1) The link between the leucine uptake pathway and PDIM is interesting but has not been characterized mechanistically. The authors discuss that PDIM presents a barrier to the uptake of nutrients and shows binding of the drug with PpsB. However it is unclear why only the leucine uptake pathway was affected. We still do not know what PpsB actually does for amino acid uptake - is it a transporter? Does semapimod binding affect its activity? Does the auxotrophic Mtb have lower PDIM levels compared to wild-type Mtb?

      (2) The authors show an interesting result where they observed antibacterial activity of semapimod against H37Rv only in vivo and not in vitro. Why do the authors think this is the basis of this observation? It is possible semapimod has an immunomodulatory effect on the host since leucine is an essential amino acid in mice. The authors could check pro-inflammatory cytokine levels in infected mouse lungs with and without drug treatment.

      (3) The authors show that the semapimod-resistant auxotroph lacks PDIM. The conclusions would be further strengthened by including validations using PDIM mutants, including del-ppsB Mtb and other genes of the PDIM locus, whether in vivo this mutant would be more susceptible (or resistant) to semapimod treatment.

      (4) Prolonged subculturing can introduce mutations in PDIM, which can be overcome by supplementing with propionate (Mullholland et al, Nat Microbiol, 2024). Did the authors also supplement their cultures with propionate? It would be interesting to see what mutations would result in Semr strains with propionate supplementation along with prolonged semapimod treatment.

      Weaknesses:

      I have summarized the limitations above in my comments. Overall, it would be helpful to provide more mechanistic details to study the connection between leucine uptake and PDIM.

    2. Author response:

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      n this manuscript, the authors used a leucine/pantothenate auxotrophic strain of Mtb to screen a library of FDA-approved compounds for their antimycobacterial activity and found significant antibacterial activity of the inhibitor semapimod. In addition to alterations in pathways, including amino acid and lipid metabolism and transcriptional machinery, the authors demonstrate that semapimod treatment targets leucine uptake in Mtb. The work presents an interesting connection between nutrient uptake and cell wall composition in mycobacteria.

      Strengths:

      The link between the leucine uptake pathway and PDIM is interesting but has not been characterized mechanistically. The authors discuss that PDIM presents a barrier to the uptake of nutrients and shows binding of the drug with PpsB. However it is unclear why only the leucine uptake pathway was affected.

      We observe interference of L-leucine, but not of pantothenate, uptake in mc2 6206 strain upon semapimod treatment. At present, we do not have any clue whether PDIM presents a barrier exclusively to the uptake of L-leucine. Further studies may shed a light on underlying mechanism(s) by which L-leucine uptake is modulated by this small molecule.

      We still do not know what PpsB actually does for amino acid uptake - is it a transporter?

      By BLI-Octet we do not find any interaction between L-leucine and PpsB. Therefore, we doubt that PpsB is a transporter of L-leucine.

      Does semapimod binding affect its activity?

      Our study suggests that semapimod treatment alters PDIM architecture which becomes restrictive to L-leucine. However, at present the exact mechanism is not clear. Further studies are required to thoroughly examine the effect of semapimod on Mtb PpsB activity and alterations in PDIM by mass spectrometry.

      Does the auxotrophic Mtb have lower PDIM levels compared to wild-type Mtb?

      As per the published report by Mulholland et al, and by vancomycin susceptibility phenotype in our study, both the strains appear to have comparable PDIM levels.

      The authors show an interesting result where they observed antibacterial activity of semapimod against H37Rv only in vivo and not in vitro. Why do the authors think this is the basis of this observation? It is possible semapimod has an immunomodulatory effect on the host since leucine is an essential amino acid in mice. The authors could check pro-inflammatory cytokine levels in infected mouse lungs with and without drug treatment.

      Semapimod inhibits production of proinflammatory cytokines such as TNF-α, IL-1β, and IL-6, which would indeed help pathogen establish chronic infection. However, a significant reduction in bacterial loads in lungs and spleen upon semapimod treatment despite inhibition of proinflammatory cytokines clearly indicates bacterial dependence on host-derived exogenous leucine during intracellular growth.

      The authors show that the semapimod-resistant auxotroph lacks PDIM. The conclusions would be further strengthened by including validations using PDIM mutants, including del-ppsB Mtb and other genes of the PDIM locus, whether in vivo this mutant would be more susceptible (or resistant) to semapimod treatment.

      PDIM is a virulence factor, and plays an important role in the intracellular survival of the TB pathogen. Mtb strains lacking PDIM are expected to show attenuated growth during infection, even without semapimod treatment. In such a case, it might be difficult to draw any conclusions about the effect of semapimod against PDIM(-) strains in vivo.

      Prolonged subculturing can introduce mutations in PDIM, which can be overcome by supplementing with propionate (Mullholland et al, Nat Microbiol, 2024). Did the authors also supplement their cultures with propionate? It would be interesting to see what mutations would result in Semr strains with propionate supplementation along with prolonged semapimod treatment.

      Considering the fact that extensive subculturing may result in loss of PDIM, we avoided prolonged subculturing of bacteria. As presented in Fig. 6b, the WT bacteria retain PDIM. While performing the initial screening of drugs, we did not anticipate such phenotype, and hence bacteria were cultured in regular 7H9-OADS medium without propionate supplementation.

      A comprehensive future study would help examining the effect of propionate on generation of semapimod resistant mutants in Mtb mc2 6206.

      Weaknesses:

      I have summarized the limitations above in my comments. Overall, it would be helpful to provide more mechanistic details to study the connection between leucine uptake and PDIM.

      Reviewer #2 (Public review):

      Summary

      This important study uncovers a novel mechanism for L-leucine uptake by M. tuberculosis and shows that targeting this pathway with 'Semapimod' interferes with bacterial metabolism and virulence. These results identify the leucine uptake pathway as a potential target to design new anti-tubercular therapy.

      Strengths

      The authors took numerous approaches to prove that L-leucine uptake of M. tuberculosis is an important physiological phenomenon and may be effectively targeted by 'Semapimod'. This study utilizes a series of experiments using a broad set of tools to justify how the leucine uptake pathway of M. tuberculosis may be targeted to design new anti-tubercular therapy.

      Weaknesses

      The study does not explain how L-leucine is taken up by M. tuberculosis, leaving the mechanism unclear. Even though 'Semapimod' binds to the PpsB protein, the relevant connection between changes in PDIM and amino acid transport remains incomplete.

      While Leucine uptake involves specific transporters in other bacteria, such transport system is not known in Mtb. By screening small molecule inhibitors, we came across a molecule, semapimod, which selectively kills the leucine auxotroph (mc2 6206), but not the WT Mtb. To understand the underlying mechanism of differential susceptibility of the WT and auxotrophic strains to this molecule, we evaluated the effect of restoration of leuCD and panCD expression on susceptibility of the auxotrophic strain to semapimod. Interestingly, our results demonstrated that upon endogenous expression of leuCD genes, mc2 6206 strain becomes resistant to killing by semapimod. In contrast, no effect of panCD expression was observed on semapimod susceptibility of mc2 6206. These findings were further substantiated by gene expression analysis of semapimod treated mc2 6206, which exhibits differential regulation of a set of genes that are altered upon leucine depletion in Mtb as well as in other bacteria. Overall results thus provide first evidence of perturbation of L-leucine uptake by semapimod treatment of the leucine auxotroph.

      To further gain mechanistic insights into the effect of semapimod on leucine uptake in Mtb, we generated the semapimod resistant strain which exhibits point mutation in 4 genes including ppsB. Interestingly, overexpression of wild-type ppsB, but not of other genes, restored susceptibility of the resistant bacteria to semapimod. Our observations that semapimod interacts with PpsB, and semapimod resistant strain accumulates mutation in PpsB resulting in loss of PDIM together support the involvement of cell-wall PDIM in regulation of L-leucine transport in Mtb.

      As mentioned above, we anticipate that semapimod treatment brings about certain modifications in PDIM which becomes more restrictive to L-leucine. A comprehensive future study will be helpful to examine the effect of semapimod on Mtb physiology.

      Also, the fact that the drug does not function on WT bacteria makes it a weak candidate to consider its usefulness for a therapeutic option.

      We agree that semapimod is not an appropriate drug candidate against TB owing to its inhibitory effect on production of proinflammatory cytokines such as TNF-α, IL-1β, and IL-6 that help pathogen establish chronic infection. However, a significant reduction in bacterial loads in lungs and spleen upon semapimod treatment despite inhibition of proinflammatory cytokines clearly indicates bacterial dependence on host-derived exogenous leucine during intracellular growth. Therefore targeting L-leucine uptake can be a novel therapeutic strategy against TB.

      Reviewer #3 (Public review):

      Agarwal et al identified the small molecule semapimod from a chemical screen of repurposed drugs with specific antimycobacterial activity against a leucine-dependent strain of M. tuberculosis. To better understand the mechanism of action of this repurposed anti-inflammatory drug, the authors used RNA-seq to reveal a leucine-deficient transcriptomic signature from semapimod challenge. The authors then measured a decreased intracellular concentration of leucine after semapimod challenge, suggesting that semapimod disrupts leucine uptake as the primary mechanism of action. Unexpectedly, however, resistant mutants raised against semapimod had a mutation in the polyketide synthase gene ppsB that resulted in loss of PDIM synthesis. The authors believe growth inhibition is a consequence of decreased accumulation of leucine as a result of an impaired cell wall and a disrupted, unknown leucine transporter. This study highlights the importance of branched-chain amino acids for M. tuberculosis survival, and the chemical genetic interactions between semapimod and ppsB indicate that ppsB is a conditionally essential gene in a medium depleted of leucine.

      The conclusions regarding the leucine and PDIM phenotypes are moderately supported by experimental data. The authors do not provide experimental evidence to support a specific link between leucine uptake and impaired PDIM production. Additional work is needed to support these claims and strengthen this mechanism of action.

      As mentioned above, overall results from this study provide first evidence of perturbation of L-leucine uptake by semapimod treatment of the leucine auxotroph. Our observations that semapimod interacts with PpsB, and semapimod resistant strain accumulates mutation in PpsB resulting in loss of PDIM together support the involvement of cell-wall PDIM in regulation of L-leucine transport in Mtb.

      As hitherto mentioned, it appears that semapimod treatment brings about certain modifications in PDIM which becomes restrictive to L-leucine. Future studies are required to gain detailed mechanistic insights into the effect of semapimod on Mtb physiology.

      Since leucine uptake and PDIM synthesis are important concepts of the manuscript, experiments would benefit from exploring other BCAAs to know if the phenotypes observed are specific to leucine, and adding additional strains to the 2D TLC experiments to provide confidence in the absence of the PDIM band.

      We thank the peer reviewer for this suggestion. We would be happy to analyse the effect of semapimod on the level of other amino acids including BCAA by mass spectrometry.

      The intriguing observation that wild-type H37Rv is resistant to semapimod but the leucine-auxotroph is sensitive should be further explored. If the authors are correct and semapimod does inhibit leucine uptake through a specific transporter or disrupted cell wall (PDIM synthesis), testing semapimod activity against the leucine-auxotroph in various concentrations of BCAAs could highlight the importance of intracellular leucine. H37Rv is still able to synthesize endogenous leucine and is able to circumvent the effect of semapimod.

      We thank the peer reviewer for this suggestion. We would explore the possibility of analysing the effect of increasing concentrations of BCAAs on mc2 6206 susceptibility to semapimod.

    1. divulgação
      • Informativo nº 766
      • 14 de março de 2023.
      • SEGUNDA TURMA
      • Processo: AREsp 2.130.619-SP, Rel. Ministro Francisco Falcão, Segunda Turma, por unanimidade, julgado em 7/3/2023, DJe 10/3/2023.

      Ramo do Direito DIREITO CIVIL

      Paz, Justiça e Instituições EficazesTema <br /> Vazamento de dados pessoais. Dados comuns e sensíveis. Dano moral presumido. Impossibilidade.

      DESTAQUE - O vazamento de dados pessoais não gera dano moral presumido.

      INFORMAÇÕES DO INTEIRO TEOR

      • Trata-se, na origem, de ação de indenização ajuizada por pessoa idosa contra concessionária de energia elétrica pleiteando indenização por danos morais decorrentes do vazamento e acesso, por terceiros, de dados pessoais.

      • O art. 5º, II, da Lei Geral de Proteção de Dados - LGPD dispõe de forma expressa quais dados podem ser considerados sensíveis e, devido a essa condição, exigir tratamento diferenciado, previsto em artigos específicos. Os dados de natureza comum, pessoais mas não íntimos, passíveis apenas de identificação da pessoa natural não podem ser classificados como sensíveis.

      • Os dados objeto da lide são aqueles que se fornece em qualquer cadastro, inclusive nos sites consultados no dia a dia, não sendo, portanto, acobertados por sigilo, e o conhecimento por terceiro em nada violaria o direito de personalidade da recorrida.

      • O vazamento de dados pessoais, a despeito de se tratar de falha indesejável no tratamento de dados de pessoa natural por pessoa jurídica, não tem o condão, por si só, de gerar dano moral indenizável. Ou seja, o dano moral não é presumido, sendo necessário que o titular dos dados comprove eventual dano decorrente da exposição dessas informações.

      • Diferente seria se, de fato, estivéssemos diante de vazamento de dados sensíveis, que dizem respeito à intimidade da pessoa natural.


      • Informativo nº 749
      • 19 de setembro de 2022.
      • QUARTA TURMA
      • Processo: REsp 1.325.938-SE, Rel. Min. Raul Araújo, Quarta Turma, por unanimidade, julgado em 23/08/2022, DJe 31/08/2022.

      Ramo do Direito DIREITO CIVIL

      Paz, Justiça e Instituições EficazesTema <br /> Matéria jornalística. Críticas jornalísticas a magistrada. Autoridade pública. Direito de informação, expressão e liberdade de imprensa. Ausência de configuração de abuso no dever de informar. Interesse público. Dano moral. Afastamento. Prevalência da liberdade de informação e de crítica.

      DESTAQUE - A divulgação de notícia ou crítica acerca de atos ou decisões do Poder Público, ou de comportamento de seus agentes, não configuram, a princípio, abuso no exercício da liberdade de imprensa, desde que não se refiram a núcleo essencial de intimidade e de vida privada da pessoa.

      INFORMAÇÕES DO INTEIRO TEOR - Esta Corte Superior estabeleceu, para situações de conflito entre a liberdade de expressão e os direitos da personalidade, entre outros, os seguintes elementos de ponderação: "(I) o compromisso ético com a informação verossímil; (II) a preservação dos chamados direitos da personalidade, entre os quais incluem-se os direitos à honra, à imagem, à privacidade e à intimidade; e (III) a vedação de veiculação de crítica jornalística com intuito de difamar, injuriar ou caluniar a pessoa (animus injuriandi vel diffamandi)" (REsp 801.109/DF, Rel. Ministro Raul Araújo, Quarta Turma, DJe de 12/03/2013).

      • Em princípio, a publicação de matéria jornalística que narra fatos verídicos ou verossímeis não caracteriza hipótese de responsabilidade civil, ainda que apresentando opiniões severas, irônicas ou impiedosas, sobretudo quando se tratar de figura pública que exerça atividade tipicamente estatal, gerindo interesses da coletividade, e que se refira a fatos de interesse geral relacionados à atividade pública desenvolvida pela pessoa noticiada.

      • A liberdade de expressão, nessas hipóteses, é prevalente, atraindo verdadeira excludente anímica, a afastar o intuito doloso de ofender a honra da pessoa a que se refere a reportagem.

      • Contudo, a análise acerca da ocorrência de abuso no exercício da liberdade de expressão, a ensejar reparação por dano moral, deve ser feita em cada caso concreto, mormente quando a pessoa envolvida for investida de autoridade pública, pois, em tese, sopesados os valores em conflito, é recomendável que se dê primazia à liberdade de informação e de crítica, como decorrência da vida em um Estado Democrático.

      • Em observância à situação fática do processo em epígrafe, a reportagem baseou-se em relatos do superintendente da Polícia Civil do Estado, acerca da deflagração de operação que investigava pessoas envolvidas com o jogo do bicho em determinado Estado, citando a atuação da autora no exercício de seu cargo público (magistrada), tendo o Tribunal local consignado expressamente que "a intenção de narrar o ocorrido esteve presente durante toda a redação do texto".

      • Nesse prisma, tem-se que a matéria jornalística relacionou-se a fatos de interesse da coletividade, os quais dizem respeito diretamente com atos da magistrada enquanto autoridade pública.

      • Assim, verifica-se que, em que pese o tom ácido da referida reportagem, com o emprego de expressões como "aberração jurídica" e "descalabro", as críticas estão inseridas no âmbito da matéria jornalística de cunho informativo, baseada em levantamentos de fatos de interesse público, sem adentrar a intimidade e a vida privada da recorrida, o que significa que não extrapola claramente o direito de crítica, principalmente porque exercida em relação a caso que ostenta gravidade e ampla repercussão e interesse social.

      • Desse modo, quando não ficar caracterizado o abuso ofensivo na crítica exercida pela parte no exercício da liberdade de expressão jornalística, deve-se afastar o dever de indenização, por força da "imperiosa cláusula de modicidade" subjacente a que alude a eg. Suprema Corte no julgamento da ADPF 130/DF.


      • Informativo nº 723
      • 7 de fevereiro de 2022.
      • TERCEIRA TURMA
      • Processo: REsp 1.961.581-MS, Rel. Min. Nancy Andrighi, Terceira Turma, por unanimidade, julgado em 07/12/2021, DJe 13/12/2021.

      Ramo do Direito DIREITO CIVIL

      Paz, Justiça e Instituições EficazesTema <br /> Direito ao esquecimento. Fatos verídicos. Exclusão de matéria jornalística. Impossibilidade.

      DESTAQUE - O direito ao esquecimento não justifica a exclusão de matéria jornalística.

      INFORMAÇÕES DO INTEIRO TEOR - O direito à liberdade de imprensa não é absoluto, devendo sempre ser alicerçado na ética e na boa-fé, sob pena de caracterizar-se abusivo. A esse respeito, a jurisprudência desta Corte Superior é consolidada no sentido de que a atividade da imprensa deve pautar-se em três pilares, a saber: (I) dever de veracidade, (II) dever de pertinência e (III) dever geral de cuidado. Ou seja, o exercício do direito à liberdade de imprensa será considerado legítimo se o conteúdo transmitido for verdadeiro, de interesse público e não violar os direitos da personalidade do indivíduo noticiado.

      • Se esses deveres não forem observados e disso resultar ofensa a direito da personalidade da pessoa objeto da comunicação, surgirá para o ofendido o direito de ser reparado.

      • No caso, consoante destacado pelo Tribunal de origem, não há dúvidas acerca da veracidade da informação divulgada. Ademais, tratando-se de fato relativo à esfera penal, revela-se presente o interesse público na notícia. Por sua vez, em que pese o recorrido tenha alegado que a notícia interferiu e interfere negativamente na sua vida profissional, não alegou que a sua divulgação pela imprensa teve o propósito de ofender a sua honra.

      • Desse modo, não houve abuso no exercício da liberdade de imprensa.

      • É preciso definir, então, se o tempo transcorrido desde a ocorrência do fato é capaz, por si só, de justificar a imposição do dever de proceder à exclusão da matéria jornalística.

      • Em algumas oportunidades, a Quarta e a Sexta Turmas desta Corte Superior se pronunciaram favoravelmente acerca da existência do direito ao esquecimento. Considerando os efeitos jurídicos da passagem do tempo, ponderou-se que o Direito estabiliza o passado e confere previsibilidade ao futuro por meio de diversos institutos (prescrição, decadência, perdão, anistia, irretroatividade da lei, respeito ao direito adquirido, ato jurídico perfeito e coisa julgada).

      • Ocorre que, em fevereiro deste ano, o Supremo Tribunal Federal definiu que o direito ao esquecimento é incompatível com a Constituição Federal (Tema 786). Assim, o direito ao esquecimento, porque incompatível com o ordenamento jurídico brasileiro, não é capaz de justificar a atribuição da obrigação de excluir a publicação relativa a fatos verídicos.


      • RE 1010606
      • Órgão julgador: Tribunal Pleno
      • Relator(a): Min. DIAS TOFFOLI
      • Julgamento: 11/02/2021
      • Publicação: 20/05/2021

      Recurso extraordinário com repercussão geral. Caso Aída Curi. Direito ao esquecimento. Incompatibilidade com a ordem constitucional. Recurso extraordinário não provido. 1. Recurso extraordinário interposto em face de acórdão por meio do qual a Décima Quinta Câmara Cível do Tribunal de Justiça do Estado do Rio de Janeiro negou provimento a apelação em ação indenizatória que objetivava a compensação pecuniária e a reparação material em razão do uso não autorizado da imagem da falecida irmã dos autores, Aída Curi, no programa Linha Direta: Justiça. 2. Os precedentes mais longínquos apontados no debate sobre o chamado direito ao esquecimento passaram ao largo do direito autônomo ao esmaecimento de fatos, dados ou notícias pela passagem do tempo, tendo os julgadores se valido essencialmente de institutos jurídicos hoje bastante consolidados. A utilização de expressões que remetem a alguma modalidade de direito a reclusão ou recolhimento, como droit a l’oubli ou right to be let alone, foi aplicada de forma discreta e muito pontual, com significativa menção, ademais, nas razões de decidir, a direitos da personalidade/privacidade. Já na contemporaneidade, campo mais fértil ao trato do tema pelo advento da sociedade digital, o nominado direito ao esquecimento adquiriu roupagem diversa, sobretudo após o julgamento do chamado Caso González pelo Tribunal de Justiça Europeia, associando-se o problema do esquecimento ao tratamento e à conservação de informações pessoais na internet. 3. Em que pese a existência de vertentes diversas que atribuem significados distintos à expressão direito ao esquecimento, é possível identificar elementos essenciais nas diversas invocações, a partir dos quais se torna possível nominar o direito ao esquecimento como a pretensão apta a impedir a divulgação, seja em plataformas tradicionais ou virtuais, de fatos ou dados verídicos e licitamente obtidos, mas que, em razão da passagem do tempo, teriam se tornado descontextualizados ou destituídos de interesse público relevante. 4. O ordenamento jurídico brasileiro possui expressas e pontuais previsões em que se admite, sob condições específicas, o decurso do tempo como razão para supressão de dados ou informações, em circunstâncias que não configuram, todavia, a pretensão ao direito ao esquecimento. Elas se relacionam com o efeito temporal, mas não consagram um direito a que os sujeitos não sejam confrontados quanto às informações do passado, de modo que eventuais notícias sobre esses sujeitos – publicadas ao tempo em que os dados e as informações estiveram acessíveis – não são alcançadas pelo efeito de ocultamento. Elas permanecem passíveis de circulação se os dados nelas contidos tiverem sido, a seu tempo, licitamente obtidos e tratados. Isso porque a passagem do tempo, por si só, não tem o condão de transmutar uma publicação ou um dado nela contido de lícito para ilícito. 5. A previsão ou aplicação do direito ao esquecimento afronta a liberdade de expressão. Um comando jurídico que eleja a passagem do tempo como restrição à divulgação de informação verdadeira, licitamente obtida e com adequado tratamento dos dados nela inseridos, precisa estar previsto em lei, de modo pontual, clarividente e sem anulação da liberdade de expressão. Ele não pode, ademais, ser fruto apenas de ponderação judicial. 6. O caso concreto se refere ao programa televisivo Linha Direta: Justiça, que, revisitando alguns crimes que abalaram o Brasil, apresentou, dentre alguns casos verídicos que envolviam vítimas de violência contra a mulher , objetos de farta documentação social e jornalística, o caso de Aida Curi, cujos irmãos são autores da ação que deu origem ao presente recurso. Não cabe a aplicação do direito ao esquecimento a esse caso, tendo em vista que a exibição do referido programa não incorreu em afronta ao nome, à imagem, à vida privada da vítima ou de seus familiares. Recurso extraordinário não provido. 7. Fixa-se a seguinte tese: “É incompatível com a Constituição a ideia de um direito ao esquecimento, assim entendido como o poder de obstar, em razão da passagem do tempo, a divulgação de fatos ou dados verídicos e licitamente obtidos e publicados em meios de comunicação social analógicos ou digitais. Eventuais excessos ou abusos no exercício da liberdade de expressão e de informação devem ser analisados caso a caso, a partir dos parâmetros constitucionais - especialmente os relativos à proteção da honra, da imagem, da privacidade e da personalidade em geral - e das expressas e específicas previsões legais nos âmbitos penal e cível”.

      Tema - 786 - Aplicabilidade do direito ao esquecimento na esfera civil quando for invocado pela própria vítima ou pelos seus familiares.

      Tese - É incompatível com a Constituição a ideia de um direito ao esquecimento, assim entendido como o poder de obstar, em razão da passagem do tempo, a divulgação de fatos ou dados verídicos e licitamente obtidos e publicados em meios de comunicação social analógicos ou digitais. Eventuais excessos ou abusos no exercício da liberdade de expressão e de informação devem ser analisados caso a caso, a partir dos parâmetros constitucionais - especialmente os relativos à proteção da honra, da imagem, da privacidade e da personalidade em geral - e as expressas e específicas previsões legais nos âmbitos penal e cível.


      JURISPRUDÊNCIA EM TESES - EDIÇÃO 224

      MARCO CIVIL DA INTERNET III - LEI N. 12.965/2014

      Edição disponibilizada em: 27/10/2023

      Edição atualizada em: 13/10/2023

      • 4) O direito ao esquecimento, entendido como a possiblidade de obstar, em razão da passagem do tempo, a divulgação de fatos ou dados verídicos e licitamente obtidos e publicados em meios de comunicação social, analógicos ou digitais, não é aplicável ao ordenamento jurídico brasileiro.

      • 5) A desindexação de conteúdos não se confunde com o direito ao esquecimento, pois não implica a exclusão de resultados, mas tão somente a desvinculação de determinados conteúdos obtidos por meio dos provedores de busca.

    1. Reviewer #2 (Public review):

      Summary:

      This study shows that type I interferon (IFN-I) signaling helps protect against mycobacterial infection. Using human gene expression data and a zebrafish model, the authors find that reduced IFN-I activity is linked to more severe disease. They also show that zebrafish lacking the IFN-I signaling gene stat2 are more vulnerable to infection due to poor macrophage migration. These results suggest a protective role for IFN-I in mycobacterial disease, challenging previous findings from other animal models.

      Strengths:

      Strengths of the manuscript include the use of human clinical samples to support relevance to disease, along with a genetically tractable zebrafish model that enables mechanistic insight.

      Weaknesses:

      (1) The manuscript presents intriguing human data showing an inverse correlation between IFN-I gene signatures and TB disease, but the findings remain correlative and may be cohort-specific. Given that the skin is not a primary site of TB and is relatively immunotolerant, the biological relevance of downregulated IFN-I-related genes in this tissue to systemic or pulmonary TB is unclear.

      (2) The reliance on stat2 CRISPants in zebrafish offers a limited view of IFN-I signaling. Including additional crispant lines targeting other key regulators (e.g., ifnar1, tyk2, irf3, irf7) would strengthen the interpretation and clarify whether the observed effects reflect broader IFN-I pathway disruption.

      (3) The conclusion that IFN-I is protective contrasts with established findings from murine and non-human primate models, where IFN-I is often detrimental. While the authors highlight species differences, the lack of functional human data and reliance on M. marinum in zebrafish limit the translational relevance. A more balanced discussion addressing these discrepancies would improve the manuscript.

      (4) Quantification of bacterial burden using fluorescence intensity alone may not accurately reflect bacterial viability. Complementary methods, such as qPCR for bacterial DNA, would provide a more robust assessment of antimicrobial activity.

      (5) Finally, the authors should clarify whether impaired macrophage recruitment in stat2 crispants results from defects in chemotaxis, differentiation, or survival, and address discrepancies between their human blood findings and prior studies.

    2. Author response:

      Public Reviews:

      Reviewer #1 (Public review):

      Summary:

      The manuscript finds a negative relationship between tuberculin skin test-induced type I interferon activity with chest X-ray tuberculosis severity in humans. This evidence is between incomplete and solid. It needs a bioinfomatics/transcriptomics reviewer to make a more insightful judgement. The manuscript demonstrates a convincing role for Stat2 in controlling Mycobacterium marinum infection in zebrafish embryos, incomplete data are presented linking reduced leukocyte recruitment to the infection susceptibility phenotype.

      Strengths:

      (1) An interesting analysis of TST response correlated with chest X-ray pathology.

      (2) Novel data on a protective role for Stat2 in a natural host-mycobacterial species infection pairing.

      We appreciate the reviewer’s positive comments.

      Weaknesses:

      (1) The transcriptional modules are very large sets of genes that do not present a clear picture of what is actually being measured relative to other biological pathways.

      The transcriptional module analysis is a major strength of our approach. These gene signatures are derived from independent experiments, most of which have been previously published/validated [1,2]. To clarify, they represent co-regulated gene sets downstream of signalling pathways. Increased number of genes in these modules increases their combinatorial specificity for a given biological pathway. In the human data, they serve as orthogonal validation for the bioinformatic analysis showing enrichment of the type I IFN pathway among TST transcriptome genes that are negatively correlated with radiographic disease severity in pulmonary TB (see Figure 2). Importantly, our modules confirm the relationship with type I IFN signalling (see Figure 2E) by discriminating from type II IFN signalling, which is not statistically significantly correlated with radiographic TB severity (see Figure S6C-E).

      (2) The link between infection-Stat2-leukocyte recruitment and containment of infection is plausible, but lacks a specific link to the first part of the manuscript.

      For clarification, the first part of the study seeks to identify immune response pathways that relate to severity of human disease, leading to the identification of type I IFN signalling. Since the human data are limited to an observational analysis in which we cannot test causality, the second part of our study uses a genetically tractable experimental model to test the hypothesis that type I IFN signalling is host-protective and explore possible mechanisms for a beneficial effect. This leads to the observation that type I IFN responses contribute to early myeloid cell recruitment to the site of infection, that has previously been shown to be crucial for containment of mycobacterial infection in zebrafish larvae. We will further evaluate the introduction and results sections to ensure a clear link between the human and zebrafish work.

      Major concerns

      (1) Line 158: The two transcriptional modules should be placed in the context of other DEG patterns. The macrophage type I interferon module, in particular, is quite large (361 genes). Can this be made more granular in terms of type I IFN ligands and STAT2-dependent genes?

      We respectfully disagree with this comment. For clarification, the 360 gene module reflects the zebrafish larval response to IFNphi1 protein [3]. Type I IFNs are known to induce hundreds of interferon stimulated genes [4]. As explained above, the size of the modules increases specificity for a given signalling pathway. In this case, we are most interested in discriminating type I and type II IFN signalling pathways that represent very different upstream biological processes. The discrimination we achieve with our modular approach is a major advance over previous reports of gene signatures in TB that do not discriminate between the two pathways. In this study, we did not discriminate between signalling downstream of type I IFN ligands and STAT2, consistent with existing literature showing that type I IFN signalling is STAT2 dependent [5,6].

      (2) The ifnphi1 injection into mxa:mCherry stat2 crispants is a nice experiment to demonstrate loss of type I IFN responsiveness. Further data is required to demonstrate if important mycobacterial control pathways (IFNy, TNF, il6?, etc) are intact in stat2 crispants before being able to conclude that these phenotypes are specific to type I IFN.

      Thank you for the positive comment. We acknowledge this point and will attempt to evaluate whether pro-inflammatory cytokine responses are intact in stat2 CRISPants by qPCR or bulk RNAseq. However, these experiments may prove inconclusive because of the limited sensitivity in this approach.

      Reviewer #2 (Public review):

      Summary:

      This study shows that type I interferon (IFN-I) signaling helps protect against mycobacterial infection. Using human gene expression data and a zebrafish model, the authors find that reduced IFN-I activity is linked to more severe disease. They also show that zebrafish lacking the IFN-I signaling gene stat2 are more vulnerable to infection due to poor macrophage migration. These results suggest a protective role for IFN-I in mycobacterial disease, challenging previous findings from other animal models.

      Strengths:

      Strengths of the manuscript include the use of human clinical samples to support relevance to disease, along with a genetically tractable zebrafish model that enables mechanistic insight.

      We welcome the reviewer’s positive summary of our study.

      Weaknesses:

      (1) The manuscript presents intriguing human data showing an inverse correlation between IFN-I gene signatures and TB disease, but the findings remain correlative and may be cohort-specific. Given that the skin is not a primary site of TB and is relatively immunotolerant, the biological relevance of downregulated IFN-I-related genes in this tissue to systemic or pulmonary TB is unclear.

      We agree with the reviewer that the observational human data are correlative. That is precisely why we extend the study to undertake mechanistic studies in a genetically tractable animal model, using M. marinum infection of zebrafish larvae. In the introduction, we already provide a detailed rationale for the strengths of the TST model to study human immune responses to a standardised mycobacterial challenge. This approach mitigates against the confounding of heterogeneity in bacterial burden and sampling different stages of the natural history of infection in conventional observational human studies. Therefore, the application of the TST is a major strength of this study. We do not understand the context in which the reviewer suggests the skin is immunotolerant. In the present study and previous work we provide molecular level analysis of the TST as a robust cell mediated immune response that reflects molecular perturbation in granuloma from the site of pulmonary TB disease 1.

      (2) The reliance on stat2 CRISPants in zebrafish offers a limited view of IFN-I signaling. Including additional crispant lines targeting other key regulators (e.g., ifnar1, tyk2, irf3, irf7) would strengthen the interpretation and clarify whether the observed effects reflect broader IFN-I pathway disruption.

      We respectfully disagree with this comment. Our objective was to test the role of type I IFN signalling in M. marinum infection of zebrafish. We show that stat2 deletion effectively disrupts type I IFN signalling (Figure S8). Therefore, we do not see a compelling rationale to evaluate other molecules in the signalling pathway.

      (3) The conclusion that IFN-I is protective contrasts with established findings from murine and non-human primate models, where IFN-I is often detrimental. While the authors highlight species differences, the lack of functional human data and reliance on M. marinum in zebrafish limit the translational relevance. A more balanced discussion addressing these discrepancies would improve the manuscript.

      We acknowledge that our findings contrast with the prevailing view in published literature to date. We will further review the discussion to see how we can elaborate on the potential strengths and weaknesses of different experimental approaches, which may underpin these discrepancies.

      (4) Quantification of bacterial burden using fluorescence intensity alone may not accurately reflect bacterial viability. Complementary methods, such as qPCR for bacterial DNA, would provide a more robust assessment of antimicrobial activity.

      We and others have previously validated the use of the quantitative measures of fluorescence, used here as a measure of bacterial load [7,8]. Importantly, our measurements do not rely purely on the total fluorescence signal, but also measures of dissemination of infection, for which we see consistent findings. It is also widely recognised that DNA measurements do not necessarily correlate well with bacterial viability. Therefore, we respectfully disagree that a PCR-based approach will add substantial value to our existing analysis.

      (5) Finally, the authors should clarify whether impaired macrophage recruitment in stat2 crispants results from defects in chemotaxis, differentiation, or survival, and address discrepancies between their human blood findings and prior studies.

      We acknowledge that these are important questions. Our data show that stat2 disruption does not impact total macrophage numbers at baseline (Figure 4A,B) and therefore do not support any effect of Stat2 signalling on steady state macrophage survival or differentiation. The downregulation of macrophage mpeg1 expression in M. marinum infection precludes long-term follow-up of these cells in the context of infection [9]. Therefore, we cannot currently test the hypothesis that Stat2 signalling may influence death of macrophages recruited to the site of infection or make them more susceptible to the cytopathic effects of direct mycobacterial infection. We will attempt to confirm using short-term time-lapse imaging that cellular migration to the site of hindbrain M. marinum infection is reduced in stat2 deficient zebrafish. On the strength of what is possible to test and the established role of type I IFNs in induction of several chemokines [10,11], the most likely effect is that Stat2 signalling increases recruitment through chemokine production. We are exploring the possibility of testing changes to the chemokine profile in stat2 CRISPants by qPCR or bulk RNAseq, but these experiments may prove inconclusive because of the limitations of sensitivity in this approach.

      We recognize that our finding of no relationship between peripheral blood type I IFN activity and severity of human TB contrasts with that of previous studies. As stated in the discussion, the most likely explanation for this is our use of transcriptional modules which reflect exclusive type I IFN responses. The signatures used in other studies include both type I and type II IFN inducible genes and therefore also reflect IFN gamma driven responses.

      Reviewer #3 (Public review):

      Summary:

      In this manuscript, the authors presented an interesting study providing an insight into the role of Type-I interferon responses in tuberculosis (TB) pathogenesis by combining transcriptome analysis of PBMCs and TST from tuberculosis patients. The zebrafish model was used to identify the changes in the innate immune cell population of macrophages and neutrophils. The findings suggested that Type-I interferon signatures inversely correlated with disease severity in the TST transcriptome data. The authors validated the observations by CRISPR-mediated disruption of stat2 (a critical transcription factor for type I interferon signaling) in zebrafish larvae, showing increased susceptibility to M. marinum infection. Traditionally, type-I interferon responses have been viewed as detrimental in mycobacterial infections, with studies suggesting enhanced susceptibility in certain mouse models. The study tried to identify and further characterize the understanding of the role of type-I interferons in TB.

      Strengths:

      Traditionally, type-I interferon responses have been viewed as detrimental in mycobacterial infections, with studies suggesting enhanced susceptibility in certain mouse models. The study tried to further understand the role of type-I interferons in TB pathogenesis.

      We thank the reviewer for their summary.

      Weaknesses:

      Though the study showed an inverse correlation of Type-I interferon with radiological features of TB, the molecular mechanism is largely unexplored in the study, which is making it difficult to understand the basis of the results shown in the manuscript by the authors.

      We respectfully disagree with this comment. The observations in the human data lead to the hypothesis that type I IFN responses may be host-protective, which we then test specifically in the zebrafish model, and explore candidate mechanisms, focussing on myeloid cell recruitment to the site of infection.

      References

      (1) Bell, L.C.K., Pollara, G., Pascoe, M., Tomlinson, G.S., Lehloenya, R.J., Roe, J., Meldau, R., Miller, R.F., Ramsay, A., Chain, B.M., et al. (2016). In Vivo Molecular Dissection of the Effects of HIV-1 in Active Tuberculosis. PLoS Pathog. 12, e1005469. https://doi.org/10.1371/journal.ppat.1005469.

      (2) Pollara, G., Turner, C.T., Rosenheim, J., Chandran, A., Bell, L.C.K., Khan, A., Patel, A., Peralta, L.F., Folino, A., Akarca, A., et al. (2021). Exaggerated IL-17A activity in human in vivo recall responses discriminates active tuberculosis from latent infection and cured disease. Sci. Transl. Med. 13, eabg7673. https://doi.org/10.1126/scitranslmed.abg7673.

      (3) Levraud, J.-P., Jouneau, L., Briolat, V., Laghi, V., and Boudinot, P. (2019). IFN-Stimulated Genes in Zebrafish and Humans Define an Ancient Arsenal of Antiviral Immunity. J. Immunol. Baltim. Md 1950 203, 3361–3373. https://doi.org/10.4049/jimmunol.1900804.

      (4) Schoggins, J.W. (2019). Interferon-Stimulated Genes: What Do They All Do? Annu. Rev. Virol. 6, 567–584. https://doi.org/10.1146/annurev-virology-092818-015756.

      (5) Blaszczyk, K., Nowicka, H., Kostyrko, K., Antonczyk, A., Wesoly, J., and Bluyssen, H.A.R. (2016). The unique role of STAT2 in constitutive and IFN-induced transcription and antiviral responses. Cytokine Growth Factor Rev. 29, 71–81. https://doi.org/10.1016/j.cytogfr.2016.02.010.

      (6) Begitt, A., Droescher, M., Meyer, T., Schmid, C.D., Baker, M., Antunes, F., Knobeloch, K.-P., Owen, M.R., Naumann, R., Decker, T., et al. (2014). STAT1-cooperative DNA binding distinguishes type 1 from type 2 interferon signaling. Nat. Immunol. 15, 168–176. https://doi.org/10.1038/ni.2794.

      (7) Stirling, D.R., Suleyman, O., Gil, E., Elks, P.M., Torraca, V., Noursadeghi, M., and Tomlinson, G.S. (2020). Analysis tools to quantify dissemination of pathology in zebrafish larvae. Sci. Rep. 10, 3149. https://doi.org/10.1038/s41598-020-59932-1.

      (8) Takaki, K., Davis, J.M., Winglee, K., and Ramakrishnan, L. (2013). Evaluation of the pathogenesis and treatment of Mycobacterium marinum infection in zebrafish. Nat. Protoc. 8, 1114–1124. https://doi.org/10.1038/nprot.2013.068.

      (9) Benard, E.L., Racz, P.I., Rougeot, J., Nezhinsky, A.E., Verbeek, F.J., Spaink, H.P., and Meijer, A.H. (2015). Macrophage-expressed perforins mpeg1 and mpeg1.2 have an anti-bacterial function in zebrafish. J. Innate Immun. 7, 136–152. https://doi.org/10.1159/000366103.

      (10) Lehmann, M.H., Torres-Domínguez, L.E., Price, P.J.R., Brandmüller, C., Kirschning, C.J., and Sutter, G. (2016). CCL2 expression is mediated by type I IFN receptor and recruits NK and T cells to the lung during MVA infection. J. Leukoc. Biol. 99, 1057–1064. https://doi.org/10.1189/jlb.4MA0815-376RR.

      (11) Buttmann, M., Merzyn, C., and Rieckmann, P. (2004). Interferon-beta induces transient systemic IP-10/CXCL10 chemokine release in patients with multiple sclerosis. J. Neuroimmunol. 156, 195–203. https://doi.org/10.1016/j.jneuroim.2004.07.016.

    1. Reviewer #1 (Public review):

      Summary:

      A fundamental technique for the identification of peptide-specific CD8 T cells is the use of fluorophore-conjugated and peptide loaded MHC tetramers. Classically, refolding of specific peptides with MHC monomers can be labour intensive, and not optimal for screening large numbers of different peptides. Hence, UV-exchanged tetramers have been developed to upscale this, however, still has some associated challenges such as UV-mediated damage to peptide complexes. Here, Pothast, C.R. et al demonstrate the efficacy of using temperature exchanged tetramers for the prevalent alleles HLA-A*03:01, A*11:01, B*07:02, and C*07:02. Building upon their previous work with HLA-A*02:01, H-2Kb, and HLA-E. They first demonstrate the complex stability of tetramers with different affinity peptides at high temperature, showing complex destabilisation can be rescued with higher affinity peptides. This is followed by an optimisation of peptide exchange temperatures, tailored for each allele. The authors then demonstrate successful binding to clonal T cell lines, and then a step further with viral peptides against PBMCs from individuals with confirmed infection history. For the latter they compare to conventional tetramers and demonstrate comparable signal.<br /> Due to the prevalence of these 4 alleles, the ease-of-handling, and short time requirements, these tetramers are likely to show high utility.

      Strengths:

      The manuscript is well-written and the results are solid, although more detail may add clarity to some of the results, in particular Figures 1 and 2. Other than the points reported below, the study uses accurate controls to demonstrate the specificity of the tetramers, and the data are convincing.

      Overall, the interpretation of the results is accurate, and the discussion is thorough. Additional comments may be included to cover potential tetramer batch variability and differences in the stability of different alleles. Specifically, whether certain alleles require higher-affinity peptides to be stable, compared to others.

      Weaknesses:

      The authors demonstrate the equivalence of temperature-exchanged tetramers to conventional ones, however, as they are an advancement on UV-exchange, it would be useful to show data on how their stability, exchange efficacy, and binding to T cell lines compare to UV-based tetramers. It would be supportive to show that temperature does not impact fluorophore intensity as well.

    2. Reviewer #2 (Public review):

      Summary:

      The majority of CD8+ T cell responses rely on the proper presentation of antigens through stable MHC-I (but not requiring a stable immunological synapse). This work highlights a new approach to build an array of stable peptide MHC-I using temperature exchange, which can be used to identify antigen-specific CD8+ T cells.

      Strengths:

      In this work, the authors have proposed an alternative method to reload the peptide MHC-I molecule. Their temperature-exchange approach is distinct from current reloadable peptide MHC technologies involving photolabile peptide, empty MHC-I (Nat Commun 11, 1314 (2020). https://doi.org/10.1038/s41467-020-14862-4), tapasin/TAPBPR chaperone-assisted (eLife 7:e40126.), enzyme exchangeable (WO2020226570) and small alcohol (Curr Res Immunol. 2022 Aug 18;3:167-174. doi: 10.1016/j.crimmu.2022.08.002) approaches.

      Weaknesses:

      However, the proposed temperature-exchange approach does not substantially improve the quality of antigen-specific T cells that can be identified using the photolabile peptide MHC-I molecules.

      The time saved using the temperature-exchange protocol may not be a pull factor as the photolabile peptide MHC-I approach is not unreasonably laborious.

    3. Reviewer #3 (Public review):

      Summary:

      The study by Pothast and colleagues outlines an extension of their previously described temperature-based MHC-I peptide exchange method on 4 common HLA alleles, to enable the generation of peptide/MCH-I tetramers for characterization of antigen-specific T cells by flow cytometry.

      Strengths:

      This work outlines a protocol for generating MHC-I tetramers on 4 common HLA allotypes, which can then be applied to monitor T cell responses by flow cytometry studies. The work provides conditional ligands for exchange on each HLA and demonstrates proof of concept studies using clonotypic T cells and CD8+ PBMCs.

      The results support that the temperature-exchanged tetramers can perform similarly to conventional tetramers in some settings.

      Weaknesses:

      Given that there are several proposed methodologies addressing the same task (including UV-mediated, disulfide-bond based stabilization of empty MHC-I conformers, and chaperone-based methods), the relevance of the proposed temperature-mediated technology is questionable.

      More specifically, important limitations of the study include:

      (1) A lack of quantification of exchanged molecules relative to molecules that retain the original placeholder peptides, or completely empty molecules present in the same sample.

      (2) A lack of validation that peptide exchange has occurred in the absence of a reporter T cell line appears to be a significant limitation of the methodology for antigen / T cell discovery.

      (3) The sub-optimal exchange efficiency relative to conventional prepared pMHC-I molecules, shown in Figure 4, is a significant limitation of the approach.

      (4) There are no data to support that exchange proceeds through the generation of empty molecules during the temperature cycle, or by peptide binding on empty molecules that are already present in the sample. Understanding the mechanism of exchange is important for the necessary improvements to the methodology.

      (5) It is possible that the temperature cycle causes protein aggregation or other irreversible changes to the sample - this should be explicitly quantified and addressed in the paper, since misfolded MHC-I molecules can lead to high levels of background staining.

      (6) These potential limitations should limit detection of low-affinity/low-avidity interactions between TCRs and their cognate pMHC antigens - this should be addressed explicitly in a model antigen setting.

      (7) The approach appears to be limited to the HLAs showing high thermal stability, which have been explored in this study. However, a large fraction of HLAs show sub-optimal thermal stabilities. It seems that explicit validation of peptide exchange would be required for any new HLA allele introduced into this process.

      (8) Whether the approach can be used to load suboptimal peptides with lower thermal stabilities that are emerging immunotherapy targets is not addressed in the present study.

      Because of these limitations, the present manuscript does not conclusively support the claim that temperature-based exchange can be used as a robust methodology to generate pMHC-I tetramers with desired peptide specificities.

      As a result, the scope of applications using these suboptimal exchanged pHLA tetramers is limited, and should be addressed with further improvements of the methodology, including better characterization of exchange efficiency, demonstration of functionality across a broader range of HLA allotypes with varying thermal stability profiles, and validation with clinically relevant low-affinity peptides that would strengthen the potential utility of this approach in immunotherapy development and basic T cell biology research.

    1. Reviewer #2 (Public review):

      Summary:

      In the manuscript by Mahen et al., entitled "Gut Microbe-Derived Trimethylamine Shapes Circadian Rhythms Through the Host Receptor TAAR5," the authors investigate the interplay between a host G protein-coupled receptor (TAAR5), the gut microbiota-derived metabolite trimethylamine (TMA), and the host circadian system. Using a combination of genetically engineered mouse and bacterial models, the study demonstrates a link between microbial signaling and circadian regulation, particularly through effects observed in the olfactory system. Overall, this manuscript presents a novel and valuable contribution to our understanding of host-microbe interactions and circadian biology. However, several sections would benefit from improved clarity, organization, and mechanistic depth to fully support the authors' conclusions.

      Strengths:

      (1) The manuscript addresses an important and timely topic in host-microbe communication and circadian biology.

      (2) The studies employ multiple complementary models, e.g., Taar5 knockout mice, microbial mutants, which enhance the depth of the investigation.

      (3) The integration of behavioral, hormonal, microbial, and transcript-level data provides a multifaceted view of the observed phenotype.

      (4) The identification of olfactory-linked circadian changes in the context of gut microbes adds a novel perspective to the field.

      Weaknesses:

      While the manuscript presents compelling data, several weaknesses limit the clarity and strength of the conclusions.

      (1) The presentation of hormonal, cytokine, behavioral, and microbiome data would benefit from clearer organization, more detailed descriptions, and functional grouping to aid interpretation.

      (2) Some transitions-particularly from behavioral to microbiome data-are abrupt and would benefit from better contextual framing.

      (3) The microbial rhythmicity analyses lack detail on methods and visualization, and the sequencing metadata (e.g., sample type, sex, method) are not clearly stated.

      (4) Several figures are difficult to interpret due to dense layouts or vague legends, and key metabolites and gene expression comparisons are either underexplained or not consistently assessed across models.

      (5) Finally, while the authors suggest a causal role for TAAR5 and its ligand in circadian regulation, the current data remain correlative; mechanistic experiments or stronger disclaimers are needed to support these claims.

    1. Reviewer #1 (Public review):

      Summary:

      This manuscript analyses primarily the effects of deleting the TgfbR1 and TgfbR2 receptors from endothelial cells at postnatal stages of vascular development and blood-retina barrier maturation in the retina. The authors find that deletion of these receptors affects vascular development in the retina, but importantly, it affects the infiltration of immune cells across the vessels in the retina. The findings demonstrate that Tgfb signaling through TgfbR1/R2 heterodimers regulates primarily the immune phenotypes of endothelial cells in addition to regulating vascular development. The data provided by the authors provide a solid support for their conclusions.

      Strengths:

      (1) The manuscript uses a variety of elegant genetic studies in mice to analyze the role of TgfbR1 and TgfbR2 receptors in endothelial cells at postnatal stages of vascular development and blood-retina barrier maturation in the retina.

      (2) The authors provide a nice comparison of the vascular phenotypes in endothelial-specific knockout of TgfbR1 and TgfbR2 in the retina (and to a lesser degree in the brain) with those from Npd KO mice (loss of Ndp/Fzd signaling) or loss of VEGF-A signaling to dissect the specific roles of Tgf signaling for vascular development in the retina.

      (3) The snRNAseq data of vessel segments from the brains of WT versus TgfbR1 -iECKO mice provides a nice analysis of pathways and transcripts that are regulated by Tgfb signaling in endothelial cells.

      Weaknesses:

      (1) The authors claim that choroidal neovascular tuft phenotypes are similar in TgfbrR1 KO and TgfbrR2 KO mice. However, the phenotypes look more severe in the TgfbrR1 KO rather than TgfbrR2 KO mice. Can the authors show a quantitative comparison of the number of choroidal neovascular tufts per whole eye cross-section in both genotypes?

      (2) In the analysis of Sulfo-NHS-Biotin leakage in the retina to assess blood-retina barrier maturation. The authors claim that there is increased vascular leakage in the TgfbR1 KO mice. However, it does not seem like Sulfo-NHS-biotin is leaking outside the vessels. Therefore, it cannot be increased vascular permeability. Can the authors provide a detailed quantification of the leakage phenotype?

      (3) The immune cell phenotyping by snRNAseq is premature, as the number of cells is very small. The authors should sort for CD45+ cells and perform single-cell RNA sequencing.

      (4) The analysis of BBB leakage phenotype in TgfbR1 KO mice needs to be more detailed and include tracers as well as serum IgG leakage.

      (5) A previous study (Zarkada et al., 2021, Developmental Cell) showed that EC-deletion of Alk5 affects the D tip cells. The phenotypes of those mice look very similar to those shown for TgfbrR1 KO mice. Are D-tip cells lost in these mutants by snRNAseq?

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      Referee #2

      Evidence, reproducibility and clarity

      Summary

      Enhancer RNAs (eRNAs) are early indicators of transcription factor (TF) activity and can identify distinct molecular subtypes and pathological outcomes in breast cancer. In this study, Patel et al. analysed 302,951 polyadenylated eRNA loci from 1,095 breast cancer patients using RNA-seq data, applying machine learning (ML) to classify eRNAs associated with specific molecular subtypes and survival. They discovered subtype-specific eRNAs that implicate both established and novel regulatory pathways and TFs, as well as prognostic eRNAs -specifically, LumA and HER2-survival- that distinguish favorable from poor survival outcomes. Overall, this ML-based approach illustrates how eRNAs reveal the molecular grammar and pathological implications underlying breast cancer heterogeneity.

      Major comments

      1. The authors define 302,951 eRNA loci based on RNA-seq data, yet it is widely known that many enhancers reside in proximity to promoters or within intronic regions (examples presented in Fig. 3B and S3). Consequently, it seems likely that reads mapped to these regions might not truly represent eRNA signals but include mRNA contamination. Could the authors clarify how they ensured that the identified eRNAs were not confounded by mRNA reads? What fraction of these enhancer loci is promoter proximal or intronic? How does H3K4me3, a well-established and standardized active promoter histone mark, behave on these loci? The reviewer considers it important to confirm that the identified eRNAs are indeed of enhancer origin rather than promoter transcripts.
      2. In Fig. 1B, the F measure (0.540) of the Basal subtype using the Logmc method contradicts its extremely high precision (1.000) and sensitivity (0.890). The authors need to clarify the exact formula or method used to compute F1 and the discrepancy in the reported metrics for this subtype and perhaps other subtypes as well.
      3. As shown in Fig. 4C, S4B, and most, if not all, tracks of Fig. S3, ER binding regions are not annotated as eRNA loci. It seems, in this reviewer's opinion, very unlikely that this is because they generally lack eRNA expression, but rather they do not express polyadenylated eRNA (typically 1D eRNA), which is captured in this dataset. The reviewer posits that these enhancers produce more transient, non-polyadenylated 2D eRNA. It has been widely documented in prior studies that ER-bound enhancers exhibit bimodal eRNA expression patterns [e.g., Li, W. et al. Functional roles of enhancer RNAs for oestrogen-dependent transcriptional activation. Nature 498, 516-520 (2013)]. Could the authors address this opinion and elaborate on how the restriction to polyadenylated transcripts might underrepresent enhancers regulated by ER and other TFs and whether this bias impacts the overall findings?
      4. Despite the unsatisfied performance of the ML approach on classifying Her2 subtypes, the hierarchical clustering performed in Fig. 2A and S2A appears to show a reasonable separation of Her2 subtypes, showing as a clustered green band. Could the authors quantitatively assess how effective this clustering results and compare that to the ML outcome? (OPTIONAL)
      5. In Fig. 4 and S4, the authors reported to have enriched binding or motif of TFs, e.g., FOXA1, AP-2, and E2A, specifically at enhancer loci with low eRNA level, which conflicts with their established roles as transcriptional activators. The reviewer asks for an address as to why these factors would be associated with basal low-eRNA regions and whether any additional data might clarify their functional role in these contexts.
      6. Regarding Fig. 4B, the authors state that "ER binding occupies only the strongest ssDNA and GRO-seq-positive sites". Firstly, the GRO-seq data quality is poor with indiscernible peaks. This may be insufficient for a qualified representation of nascent eRNA expression. More importantly, it appears each heatmap is ranked independently, so top loci for ssDNA are not necessarily top loci for GRO-seq, ER, Pol-II, or H3K27ac. The reviewer requests clarification on how the authors plot these heatmaps and questions whether the statement is supported by the analysis as presented.
      7. In Fig. S4B and the third plot of 4C, the averaged histogram of ER binding appears in multiple sharp peaks with drastic asymmetric positioning around the enhancer centre, which is highly atypical of most published ER ChIP-seq profiles. Could the authors discuss possible "spatial syntax" or directional patterns of ER binding in relation to eRNA loci and cite any literature showing a similar pattern? Further evidence is required to substantiate these observations, as they are remarkably unique.

      Minor comments

      1. When introducing eRNAs, the reviewer recommends mentioning that 1) eRNA levels correlate with enhancer activity and 2) eRNA expression precedes target gene transcription, thus reflecting upstream regulatory events. Relevant references include: Arner, E. et al. Transcribed enhancers lead waves of coordinated transcription in transitioning mammalian cells. Science 347, 1010-1014 (2015); Carullo, N. V. N. et al. Enhancer RNAs predict enhancer-gene regulatory links and are critical for enhancer function in neuronal systems. Nucleic Acids Res. 48, 9550-9570 (2020); Kaikkonen, Minna U. et al. Remodeling of the Enhancer Landscape during Macrophage Activation Is Coupled to Enhancer Transcription. Mol. Cell 51, 310-325 (2013).
      2. H3K27ac is used initially to define these regulatory loci, and like eRNAs, H3K27ac also varies among patients. Which H3K27ac dataset(s) were used initially, and could this approach potentially overlook patient-specific enhancers? (OPTIONAL)
      3. In addition to the overall metrics displayed in Fig. 2B, could the authors provide precision and sensitivity values for LumA and LumB separately under the Logmc method, given the observation in Fig. 2E that LumA and LumB are not well separated in the UMAP projection?
      4. Could the author elaborate, in the discussion session, on why there is a substantial difference in ML performance depending on whether InfoGain or Logmc is used?
      5. How does the expression pattern of Basal high, Basal low, Her2, and Lum eRNA clusters behave differentially in Basal, Her2, and LumA/B subtypes? Are Basal high eRNAs downregulated in Her2 or Lum subtypes, and vice versa? Since many downstream analyses rely on these eRNA clusters, it is suggested to include a heatmap and/or boxplot that displays how each eRNA category is expressed in each subtype to confirm that these definitions are consistent.

      Referee cross-commenting

      I share Reviewer #1's opinion that the manuscript should assess whether mRNA or eRNA is the stronger predictor of breast cancer subtypes and clinical outcomes. It will greatly improve the novelty if eRNA is shown to be a better indicator for cancer characterization.

      Also, I strongly concur with Reviewer #3 that the current informatics approach is superficial and that several conclusions are contentious. The authors need to resolve the inconsistencies in their ML statistics and the potentially misleading interpretations of the ChIP‑seq and motif‑enrichment results.

      It is further recommended that, building Reviewer #3's comment, the study integrate eRNA signatures with their proximal genes to address 1) whether genes located near these enhancers are differentially expressed-and correlated with enhancer activity-across cancer subtypes, and 2) whether it provides insights into understanding the enhancer-gene regulatory architecture in a subtype-specific context.

      Significance

      General Assessment

      This study provides insights into the potential use of eRNA to classify breast cancer subtypes and refine prognostic markers. A strength is the integration of large-scale RNA-seq data with machine learning to identify eRNA signatures in biologically-meaningful patient samples, revealing both established and novel TF networks. The study also discovered eRNA clusters that correlate with the survival of patients, thus providing strong clinical implications. However, the ML approach yields several inconsistencies-for instance, unsatisfactory classification results for the Her2 subtype as well as the confused statistical metrics in the results. Furthermore, the ML model struggles to differentiate more nuanced molecular classes (e.g., LumA vs. LumB) and higher-level histological subtypes (e.g., lobular vs. ductal), thus limiting its power to dissect more delicate pathological and molecular mechanisms. Another limitation worth noting of this ML approach is the exclusive use of only polyadenylated eRNAs via RNA-seq, which excludes perhaps the more prominent 2D eRNA expressed in regulatory enhancers. Moreover, certain datasets appear to be of suboptimal quality, leading to assertions that would benefit from additional supporting evidence. Altogether, while the study offers a promising angle on eRNA-based tumor stratification, more robust experimental validations are needed to resolve inconsistencies and clarify the mechanistic underpinnings.

      Advance

      Conceptually, the study highlights the potential for eRNA-based signatures to capture regulatory variation beyond classical markers. However, the utility of these signatures is constrained by the focus on polyadenylated transcripts alone, likely underrepresenting key enhancer regions, and certain evidence presented in this study is not substantial enough to support some statements. While the work adds an important dimension to the understanding of enhancer biology in breast cancer, the resulting insights are partly hampered by limitations in data coverage and quality.

      Audience

      The primary audience includes cancer epigenetics, functional genomics, and bioinformatics researchers who are interested in leveraging eRNAs as biomarkers and dissecting complex regulatory networks in breast cancer. Clinically oriented scientists focusing on molecular diagnostics may also find relevance in the authors' approach to stratify subtypes and outcomes. The research is most relevant to a specialized audience within basic and translational cancer genomics, as well as computational biology groups interested in eRNA analysis.

      Field of Expertise

      I evaluate this manuscript as a researcher specializing in cancer epigenetics, functional genomics, and NGS-based data analysis. Parts of the manuscript touching on clinical outcome measures may require additional review from practicing oncologists.

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      Reply to the reviewers


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

      In this manuscript the authors have done cryo-electron tomography of the manchette, a microtubule-based structure important for proper sperm head formation during spermatogenesis. They also did mass-spectrometry of the isolated structures. Vesicles, actin and their linkers to microtubules within the structure are shown.

      __We thank the reviewer for the critical reading of our manuscript; we have implemented the suggestions as detailed below, which we believe indeed improved the manuscript. __

      Major:

      The data the conclusions are based on seem very limited and sometimes overinterpreted. For example, only one connection between actin and microtubules was observed, and this is thought to be MACF1 simply based on its presence in the MS.

      __We regret giving the impression that the data is limited. We in fact collected >100 tilt series from 3 biological replicas for the isolated manchette. __

      __In the revised version, we added data from in-situ studies showing vesicles interacting with the manchette (as requested below, new Fig. 1). __

      Specifically, for the interaction of actin with microtubule we added more examples (Revised Fig. 6) and we toned down the discussion related to the relevance of this interaction (lines 193-194, 253-255). MACF1 is mentioned only as a possible candidate in the discussion (line 254).

      Another, and larger concern, is that the authors do a structural study on something that has been purified out of the cell, a process which is extremely disruptive. Vesicles, actin and other cellular components could easily be trapped in this cytoskeletal sieve during the purification process and as such, not be bona fide manchette components. This could create both misleading proteomics and imaging. Therefore, an approach not requiring extraction such as high-pressure freezing, sectioning and room-temperature electron tomography and/or immunoEM on sections to set aside this concern is strongly recommended. As an additional bonus, it would show if the vesicles containing ATP synthase are deformed mitochondria.

      __We recognise the concern raised by the reviewer. __

      __To alleviate this concern, we added imaging data of manchettes in-situ that show vesicles, mitochondria and filaments interacting with the manchette (new Fig. 1), essentially confirming the observations that were made on the isolated manchette. __

      __The benefits of imaging the isolated manchette were better throughput (being able to collect more data) and reaching higher resolution allowing to resolve unequivocally the dynein/dynactin and actin filaments. __

      Minor: Line 99: "to study IMT with cryo-ET, manchettes were isolated ...(insert from which organism)..."

      __Added in line 102 in the revised version. __

      Line 102 "...demonstrating that they can be used to study IMT".. can the authors please clarify?

      This paragraph was revised (lines 131-137), we hope it is now more clear.

      Line 111 "densities face towards the MT plus-end" How can a density "face" anywhere? For this, it needs to have a defined front and back.

      Microtubule motor proteins (kinesin and dynein) are often attached to the microtubules with an angle and dynactin and cargo on one side (plus end). We rephrased this part and removed the word “face” in the revised version to make it more clear (lines 161-162).

      Line 137: is the "perinuclear ring" the same as the manchette?

      The perinuclear ring is the apical part of the manchette that connects it to the nucleus. We added to the revised version imaging of the perinuclear ring with observations on how it changes when the manchette elongates (new Fig. 2).

      Figure 2B: How did the authors decide not to model the electron density found between the vesicle and the MT at 3 O'clock? Is there no other proteins with a similar lollipop structure as ATP synthase, so that this can be said to be this protein with such certainty?

      __The densities connecting the vesicles to the microtubules shown in (now) Fig. 4D are not consistent enough to be averaged. __

      __The densities resembling ATP synthase are inside the vesicles. Nevertheless, we have decided to remove the averaging of the ATP synthases from the revised manuscipt as they are not of great importance for this manuscript. Instead, the new in-situ data clearly show mitochondria (with their characteristic double membrane and cristae) interacting with manchette microtubule (new Fig 1C). __

      Line 189: "F-actin formed organized bundles running parallel to mMTs" - this observation needs confirming in a less disrupted sample.

      __Phalloidin (actin marker) was shown before to stain the manchette (PMID: 36734600). As actin filaments are very thin (7 nm) they are very hard to observe in plastic embedded EM. __

      In the in-situ data we added to the revised manuscipt (new Fig 1D), we observe filaments with a diameter corresponding to actin. In addition, we added more examples of microtubules interacting with actin in isolated manchette (new Fig. 6 E-K).

      Line 242 remove first comma sign.

      Removed.

      Line 363 "a total of 2 datasets" - is this manuscript based on only two tilt-series? Or two datasets from each of the 4 grids? In any case, this is very limited data.

      We apologise for not clearly providing the information about the data size in the original manuscipt. The data is based on three biological replicas (3 animals). We collected more than 100 tomograms of different regions of the manchettes. As such, we would argue that the data is not limited per se.

      Reviewer #1 (Significance (Required)):

      The article is very interesting, and if presented together with the suggested controls, would be informative to both microtubule/motorprotein researchers as well as those trying studying spermatogenesis.

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

      The manchette appears as a shield-like structure surrounding the flagellar basal body upon spermiogenesis. It consists of a number of microtubules like a comb, but actin (Mochida et al. 1998 Dev. Biol. 200, 46) and myosin (Hayasaka et al. 2008 Asian J. Androl. 10, 561) were found, suggesting transportation inside the manchette. Detailed structural information and functional insight into the manchette was still awaited. There is a hypothesis called IMT (intra-machette transport) based on the fact that machette and IFT (intraflagellar transport) share common components (or homologues) and on their transition along the stages of spermiogenesis. While IMT is considered as a potential hypothesis to explain delivery of centrosomal and flagellar components, no one has witnessed IMT at the same level as IFT. IMT has never been purified, visualized in motion or at high resolution. This study for the first time visualized manchette using high-end cryo-electron tomography of isolated manchettes, addressing structural characterization of IMT. The authors successfully microtubular bundles, vesicles located between microtubules and a linker-like structure connecting the vesicle and the microtubule. On multilamellar membranes in the vesicles they found particles and assigned them to ATPase complexes, based on intermediate (~60A) resolution structure. They further identified interesting structures, such as (1) particles on microtubules, which resemble dynein and (2) filaments which shows symmetry of F-actin. All the molecular assignments are consistent with their proteomics of manchettes.

      __We thank the reviewer for highlighting the novelty of our study.____ __

      Their assignment of ATPase will be strengthened by MS data, if it proves absence of other possible proteins forming such a membrane protein complex.

      All the ATPase components were indeed found in our proteomics data. Nevertheless, we have decided to remove the averaging of the ATPase as it does not directly relate to IMT, the focus of this manuscript.

      They discussed possible role of various motor proteins based on their abundance (Line 134-151, Line 200). This makes sense only with a control. Absolute abundance of proteins would not necessarily present their local importance or roles. This reviewer would suggest quantitative proteomics of other organelles, or whole cells, or other fractions obtained during manchette isolation, to demonstrate unique abundance of KIF27 and other proteins of their interest.

      We agree with the reviewer that absolute abundance does not necessarily indicate importance or a role. As such, we removed this part of the discussion from the revised manuscript.

      A single image from a tomogram, Fig.6B, is not enough to prove actin-MT interaction. A gallery and a number (how many such junctions were found from how many MTs) will be necessary.

      We agree that one example is not enough. In the new Fig. 6E-K, we provide a gallery of more examples. We have revised the text to reflect the point that these observations are still rare and more data will be needed to quantify this interaction (Lines 253-254).

      Minor points: Their manchette purification is based on Mochida et al., which showed (their Fig.2) similarity to the in vivo structure (for example, Fig.1 of Kierszenbaum 2001 Mol. Reproduc. Dev. 59, 347). Nevertheless, since this is not a very common prep, it is helpful to show the isolated manchette’s wide view (low mag cryo-EM or ET) to prove its intactness.

      We thank the reviewer for this suggestion, in the revised version, new Fig. 2 provides a cryo-EM overview of purified manchette from different developmental stages.

      Line 81: Myosin -> myosin (to be consistent with other protein names)

      Corrected.

      This work is a significant step toward the understanding of manchettes. While the molecular assignment of dynein and ATPase is not fully decisive, due to limitation of resolution (this reviewer thinks the assignment of actin filament is convincing, based on its helical symmetry), their speculative model still deserves publication.

      Reviewer #2 (Significance (Required)):

      This work is a significant step toward the understanding of manchettes. While the molecular assignment of dynein and ATPase is not fully decisive, due to limitation of resolution (this reviewer thinks the assignment of actin filament is convincing, based on its helical symmetry), their speculative model still deserves publication.

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

      ->Summary:

      The manchette is a temporary microtubule (MT)-based structure essential for the development of the highly polarised sperm cell. In this study, the authors employed cryo-electron tomography (cryo-ET) and proteomics to investigate the intra-manchette transport system. Cryo-EM analysis of purified rat manchette revealed a high density of MTs interspersed with actin filaments, which appeared either bundled or as single filaments. Vesicles were observed among the MTs, connected by stick-like densities that, based on their orientation relative to MT polarity, were inferred to be kinesins. Subtomogram averaging (STA) confirmed the presence of dynein motor proteins. Proteomic analysis further validated the presence of dynein and kinesins and showed the presence of actin crosslinkers that could bundle actin filaments. Proteomics data also indicated the involvement of actin-based transport mediated by myosin. Importantly, the data indicated that the intraflagellar transport (IFT) system is not part of the intra-manchette transport mechanism. The visualisation of motor proteins directly from a biological sample represents a notable technical advancement, providing new insights into the organisation of the intra-manchette transport system in developing sperm.

      We thank the reviewer for summarising the novelty of our observations.

      -> Are the key conclusions convincing? Below we comment on three main conclusions. MT and F-actin bundles are both constituents of the manchette While the data convincingly shows that MT and F-actin are part of the manchette, one cannot conclude from it that F-actin is an integral part of the manchette. The authors would need to rephrase so that it is clear that they are speculating.

      We have rephrased our statements and replaced “integral” with ‘actin filaments are associated’. Of note previous studies suggested actin are part of the manchette including staining with phalloidin (PMID: 36734600, PMID: 9698455, PMID: 18478159) and we here visualised the actin in high resolution.

      The transport system employs different transport machinery on these MTs Proteomics data indicates the presence of multiple motor proteins in the manchette, while cryo-EM data corroborates this by revealing morphologically distinct densities associated with the MTs. However, the nature of only one of these MT-associated densities has been confirmed-specifically, dynein, as identified through STA. The presence of kinesin or myosin in the EM data remains unconfirmed based on just the cryo-ET density, and therefore it is unclear whether these proteins are actively involved in cargo transport, as this cannot be supported by just the proteomics data. In summary, we recommend that the authors rephrase this conclusion and avoid using the term "employ".

      We agree that our cryo-ET only confirmed the motor protein dynein. As such, we removed the term employ and rephrased our claims regarding the active transport and accordingly changed the title.

      Dynein mediated transport (Line 225-227) The data shows that dynein is present in the manchette; however, whether it plays and active role in transport cannot be determined from the cryo-ET data provided in the manuscript, as it does not clearly display a dynein-dynactin complex attached to cargo. The attachment to cargo is also not revealed via proteomics as no adaptor proteins that link dynein-dynactin to its cargo have been shown.

      A list of cargo adaptor proteins were found in our proteomics data but we agree that cryo-ET and proteomics alone cannot prove active transport. As such we toned down the discussion about active transport (lines 212-220).

      -> Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

      F-actin • In the abstract, the authors state that F-actin provides tracks for transport as well as having structural and mechanical roles. However, the manuscript does not include experiments demonstrating a mechanical role. The authors appear to base this statement on literature where actin bundles have been shown to play a mechanical role in other model systems. We suggest they clarify that the mechanical role the authors suggest is speculative and add references if appropriate.

      __ ____We removed the claim about the mechanical role of the actin from the abstract and rephrased this in the discussion to suggest this role for the F-actin (lines 242-243).__

      • Lines 15,92, 180 and 255: The statement "Filamentous actin is an integral part of the manchette" is misleading. While the authors show that F-actin is present in their purified manchette structures, whether it is integral has not been tested. Authors should rephrase the sentence.

      We removed the word integral.

      • To support the claim that F-actin plays a role in transport within the manchette, the authors present only one instance where an unidentified density is attached to an actin filament. This is insufficient evidence to claim that it is myosin actively transporting cargo. Although the proteomics data show the presence of myosin, we suggest the authors exercise more caution with this claim.

      We agree that our data do not demonstrate active transport as such we removed that claim. We mention the possibility of cargo transport in the discussion (lines 250-255).

      • The authors mention the presence of F-actin bundles but do not show direct crosslinking between the F-actin filaments. They could in principle just be closely packed F-actin filaments that are not necessarily linked, so the term "bundle" should be used more cautiously.

      We do not assume that a bundle means that the F-actin filaments are crosslinked. A bundle simply indicates the presence of multiple F-actin filaments together. We rephrased it to call them actin clusters.

      Observations of dynein • Relating to Figure 2B: From the provided image it is not clear whether the density corresponds to a dynein complex, as it does not exhibit the characteristic morphological features of dynein or dynactin molecules.

      We indeed do not claim that the densities in this figure are dynein or dynactin. __We revised this paragraph and hope that it is now more clear (lines 135-137). __

      • Lines 171-172 and Figure 4: It is well established that dynein is a dimer and should always possess two motor domains. The authors have incorrectly assumed they observed single motor heads, except possibly in Figure 4A (marked by an arrow). In all other instances, the dynein complexes show two motor domains in proximity, but these have not been segmented accurately. Furthermore, the "cargos" shown in grey are more likely to represent dynein tails or the dynactin molecule, based on comparisons with in vitro structures of these complexes (see references 1-3).

      We thank the reviewer for this correction. We improved the annotations in the figure and revised the text to clarify that we identified dimers of dynein motor heads (lines 140-144). We further added a projection of a dynein dynactin complex to compare to the observation on the manchette (new Fig. 5E). We further changed claims on the presence of protein cargo to the presence of dynein/dynactin that allows cargo tethering based on the presence of cargo adaptors in the proteomics data.

      • Lines 21, 173, and 233 mention cargos, but as noted above, it seems to be parts of the dynein complex the authors are referring to.

      This was corrected as mentioned above.

      • Panel 4B appears to show a dynein-dynactin complex, but whether there is a cargo is unclear and if there is it should be labelled accordingly. To assessment of whether there is any cargo bound to the dynein-dynactin complex a larger crop of the panel would be helpful In summary, we recommend that the authors revisit their segmentations in Figures 2B and 4, revise their text based on these observations, and perform quantification of the data (as suggested in the next section).

      We thank the reviewers for sharing their expertise on dynein-dynactin complexes. We have revised the text as detailed above and excluded the assignment of any cargo, as we cannot (even from larger panels) see a clear association of cargo. We have made clear that we only refer to dynein dynactin with the capability of linking cargo based on the presence of proteomics data. We have removed claims on active transport with dynein.

      Dynein versus kinesin-based transport The calculation presented in lines 147-151 does not account for the fact that both the dynein-dynactin complex and kinesin proteins require cargo adaptors to transport cargo. Additionally, the authors overlook the possibility that multiple motors could be attached to a single cargo. If the authors did not observe this, they should explicitly mention it to support their argument. In short, the calculations are based on an incorrect premise, rendering the comparison inaccurate. Unless the authors have identified any dynein-dynactin or kinesin cargo adaptors in their proteomics data which could be used for such a comparison, we believe the authors lack sufficient data to accurately estimate the "active transport ratio" between dynein and kinesin.

      Even though we detect cargo adaptors in our proteomics, we agree that calculating relative transport based only on the proteomics can be inaccurate as such we removed absolute quantification and comparison between dynein and kinesin-based IMT.

      • Would additional experiments be essential to support the claims of the paper?

      F-actin distance and length distribution • To support the claim that F-actin is bundled (line 189), could the authors provide the distance between each F-actin filament and its neighbours? Additionally, could they compare the average distance to the length of actin crosslinkers found in their proteomics data, or compare it to the distances between crosslinked F-actin observed in other research studies?

      We measured distances between the actin filaments and added a plot to new Fig 6.

      • While showing that F-actin is important for the manchette would require cellular experiments, authors could provide quantification of how frequently these actin structures are observed in comparison to MTs to support their claims that these actin filaments could be important for the manchette structure.

      We agree that claims on the role and function of actin in the manchette require cellular experiments that are beyond the scope of this study. Absolute quantification of the ratio between MTs and actin from cryoET is very hard and will be inaccurate as the manchette cannot be imaged as a whole due to its size and thickness. The ratio we have is based on the relative abundance provided by the proteomics (Fig. 5F).

      • In line 193, the authors claim that the F-actin in bundles appears too short for transport. Could they provide length distributions for these filaments? This might provide further support to their claim that individual F-actin filaments can serve as transport tracks (line 266).

      __In addition to the limitation mentioned in the previous point, quantification of length from high magnification imaging will likely be inaccurate as the length of the actin in most cases is bigger than the field of view that is captured. Nevertheless, we removed the claim about the actin being too short for transport. __

      • Could the authors also quantify the abundance of individual F-actin filaments observed, compared to MTs and F-actin bundles, to support the idea that they could play a role in transport?

      As explained for the above points absolute quantification of the ratio between MTs and actin is not feasible from cryoET data that cannot capture all of the manchette in high enough resolution to resolve the actin.

      • In the discussion, the authors mention "interactions between F-actin singlets and mMTs" (line 269), yet they report observing only one instance of this interaction (lines 210 and 211). Given the limited data, they should refer to this as a single interaction in the discussion. The scarcity of data raises questions about how representative this event truly is.

      We agree that one example is not enough. In the new Fig. 6E-K, we provide a gallery of more examples as also requested by reviewers 1 and 2. We have also revised the text to reflect the point that these observations are still rare (Lines 190-194).

      Quantifications for judgement of representativity The authors should quantify how often they observed vesicles with a stick-like connection to MTs (lines 106-107); this would strengthen the interpretation of the density, as currently only one example is shown in the manuscript (Figure 4A). If possible, they could show how many of them are facing towards the MT plus end.

      __As mentioned in the text (lines 135-137), the linkers connecting vesicles to MTs were irregular and so we could not interpret them further this is in contrast to dynein that were easily recognisable but were not associated with vesicles. __

      Dynein quantifications • The authors are recommended to quantify how many dynein molecules per micron of MT they observe and how often they are angled with their MT binding domain towards the minus-end.

      As the manchette is large and highly dense any quantification will likely be biased towards parts of the manchette that are easier to image, for example the periphery. As such we do not think quantifying the dynein density will yield meaningful insight.

      • Could the authors quantify how many dynein densities they found to be attached to a (vesicle) cargo, if any (line 175)? They could show these observations in a supplementary figure.

      We did not observe any case of a connection between a vesicle and dynein motors, we edited this sentence to be more clear on that.

      • For densities that match the size and location of dynein but lack clear dynein morphology (as seen in Figure 2B), could the authors quantify how many are oriented towards the MT minus end?

      We had many cases where the connection did not have a clear dynein morphology, and as the morphology is not clear, it is impossible to make a claim about whether they are oriented towards the minus end.

      Artefacts due to purification: Authors should discuss if the purification could have effects on visualizing components of the manchette. For example, if it has effect on the MTs and actin structure or the abundance/structure of the motor protein complexes (bound to cargo or isolated).

      We have followed a protocol that was published before and showed the overall integrity of the manchette. Nevertheless, losing connections between manchette and other cellular organelles are expected. To address this point, we added in-situ data (new Fig 1) showing manchette in intact spermatids interacting with vesicles and mitochondria, as well as overviews of manchettes (new Fig 2), the text was revised accordingly.

      • Are the experiments adequately replicated and statistical analysis adequate? The cryo-ET data presented in the manuscript is collected using two separate sample preparations. Along with the quantifications of the different observations suggested above which will help the reader assess how abundant and representative these observations are, the authors could further strengthen their claims by acquiring data from a third sample preparation and then analysing how consistent their observations are between different purifications. This however could be time consuming so it is not a major requirement but recommended if possible within a short time frame.

      We regret not explicitly mentioning our data set size, it was added now to the revised version. In essence, the data is based on three biological replicas (3 animals). We collected more than 100 tomograms of different regions of the manchettes. We provided in the revised version more observations (new Fig 1, 2, 4B-C and 6E-K).

      • Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

      Most of the comments deal with either modifying the text or analysing the data already presented, so the revision could be done with 1-3 months.


      Minor comments: - Specific experimental issues that are easily addressable. 1) Could the authors state how many tilt series were collected for each dataset/independent sample preparation? We recommend that they upload their raw data or tomograms to EMPAIR.

      We added this information in the material and methods.

      2) It is not clear to me if the same sample was used for cryo-ET and proteomics. Could the authors clarify how comparable the sample preparation for the cryo-ET and proteomics data is or if the same sample was used for both. If there is a discrepancy between these preparations, they would need to discuss how this can affect comparing observations from cryo-ET and mass spectrometry. Ideally both samples should be the same.

      After sample preparation the manchettes were directly frozen on grids. The rest of the samples was used for proteomics. Consequently, EM and MS data were acquired on the same samples. We clarified this in the text (lines 327-328).

      • Are prior studies referenced appropriately? We recommend including additional references to support the claim that F-actin has a mechanical role (line 242). Could the authors compare their proteomics data to other mass spectrometry studies conducted on the Manchette (for example, see reference 4)?

      We added the comparison but it is important to point out that in reference 4 the manchettes were isolated from mice testes.

      • Are the text and figures clear and accurate? Text: We do not see the necessity of specifying the microtubules (MTs) in the data as "manchette MTs" or "mMTs" rather than simply "MTs". However, we recommend that the authors use either "MT" or "mMT" consistently throughout the manuscript.

      We changed to only MTs.

      The authors appear to refer to both dynein-1 (cytoplasmic dynein) and dynein-2 (axonemal dynein or IFT dynein). To avoid confusion, it is important that the authors clearly specify which dynein they are referring to throughout the text. This is particularly relevant as the study aims to demonstrate that IFT is not part of the manchette transport system.

      • Introduction: In the third paragraph (lines 59-75), the authors should specify that they are referring to dynein-2, which is distinct from cytoplasmic dynein discussed in the previous paragraph (lines 44-58).

      We specify the respective dyneins in the text (line 66,140-141,145).

      • Figure 4D: The authors could fit a dynein-1 motor domain instead of a dynein-2 into the density to stay consistent with the fact that the density belongs to cytoplasmic dynein-1.

      __We changed the figure and fitted a cytosolic dynein-1 structure (5nvu) instead. __

      Figures: • Figure 2B: The legend mentions a large linker complex; however, this may correspond to two or three separate densities.

      We have addressed this and changed the wording.

      • Figure 4: please revisit the segmentation of this whole figure based on previous comments.

      __We revised as suggested. __

      • Figures 1, 2, 4, 5, and 6: It would be helpful to state in the legends that the tomograms are denoised. There are stripe-like densities visible in the images (e.g., in the vesicle in Figure 2B). Do these artefacts also appear in the raw data?

      As stated in the Methods section, tomograms were generally denoised with CryoCare for visualisation purposes. The “stripe-like densities” are artefacts of the gold fiducials used for tomogram alignment and appear in the raw data (before denoising).

      • Do you have suggestions that would help the authors improve the presentation of their data and conclusions? We suggest revising the paragraph title "Dynein-mediated cargo along the manchette" (line 165) to "Dynein-mediated cargo transport along the manchette".

      __We have changed this in the revised version. __

      We recommend that the authors provide additional evidence to support the interpretation that the observed EM densities correspond to motor proteins. Specifically: • Include scale bars or reference lines indicating the known dimensions of motor proteins, based on previous data, to demonstrate that the observed densities match the expected size.

      The dynein structure is provided for reference. We also added the cytosolic dynein–dynactin as a reference (Fig 5E).

      • Make direct comparisons to existing EM data and highlight morphological similarities.

      We have added a comparison to existing data (Fig 5E).

      In the discussion (lines 249-254), the authors could speculate on alternative roles for the IFT components in the manchette, particularly if they are not part of the IFT trains. We also suggest rephrasing the claim in line 266 to make it more speculative in tone.

      __We have addressed this in the revised version (lines 221-230). __

      Finally, a schematic overview of the manchette ultrastructure in a spermatid would greatly aid the reader in understanding the material presented.

      We now include a graphical abstract and overviews of isolated manchettes on cryo-EM grids.

      References: 1. Chowdhury, S., Ketcham, S., Schroer, T. et al. Structural organization of the dynein-dynactin complex bound to microtubules. Nat Struct Mol Biol 22, 345-347 (2015). https://doi.org/10.1038/nsmb.2996

      1. Grotjahn, D.A., Chowdhury, S., Xu, Y. et al. Cryo-electron tomography reveals that dynactin recruits a team of dyneins for processive motility. Nat Struct Mol Biol 25, 203-207 (2018). https://doi.org/10.1038/s41594-018-0027-7

      2. Chaaban, S., Carter, A.P. Structure of dynein-dynactin on microtubules shows tandem adaptor binding. Nature 610, 212-216 (2022).https://doi.org/10.1038/s41586-022-05186-y

      3. W. Hu, R. Zhang, H. Xu, Y. Li, X. Yang, Z. Zhou, X. Huang, Y. Wang, W. Ji, F. Gao, W. Meng, CAMSAP1 role in orchestrating structure and dynamics of manchette microtubule minus-ends impacts male fertility during spermiogenesis, Proc. Natl. Acad. Sci. U.S.A. 120 (45) e2313787120, https://doi.org/10.1073/pnas.2313787120 (2023).

      Reviewer #3 (Significance (Required)):

      This study employs cryo-electron tomography (cryo-ET) and proteomics to elucidate the architecture of the manchette. It advances our understanding of the components involved in intracellular transport within the manchette and introduces the following technical and conceptual innovations:

      a) Technical Advances: The authors have visualized the manchette at high resolution using cryo-ET. They optimized a purification pipeline capable of retaining, at least partially, the transport machinery of the manchette. Notably, they observed dynein and putative kinesin motors attached to microtubules-a significant achievement that, to our knowledge, has not been reported previously.

      b) Conceptual Advances: This study provides novel insights into spermatogenesis. The findings suggest that intraflagellar transport (IFT) is unlikely to play a role at this stage of sperm development while shedding light on alternative transport systems. Importantly, the authors demonstrate that actin filaments organize in two distinct ways: clustering parallel to microtubules or forming single filaments.

      This work is likely to be of considerable interest to researchers in sperm development and structural biology. Additionally, it may appeal to scientists studying motor proteins and the cytoskeleton.

      We thank the reviewers for appreciating the significance and novelty of our study.

      The reviewers possess extensive expertise in in situ cryo-electron tomography and single-particle microscopy, including work on dynein-based complexes. Collectively, they have significant experience in the field of cytoskeleton-based transport.

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

      Learn more at Review Commons


      Referee #3

      Evidence, reproducibility and clarity

      Summary:

      The manchette is a temporary microtubule (MT)-based structure essential for the development of the highly polarised sperm cell. In this study, the authors employed cryo-electron tomography (cryo-ET) and proteomics to investigate the intra-manchette transport system. Cryo-EM analysis of purified rat manchette revealed a high density of MTs interspersed with actin filaments, which appeared either bundled or as single filaments. Vesicles were observed among the MTs, connected by stick-like densities that, based on their orientation relative to MT polarity, were inferred to be kinesins. Subtomogram averaging (STA) confirmed the presence of dynein motor proteins. Proteomic analysis further validated the presence of dynein and kinesins and showed the presence of actin crosslinkers that could bundle actin filaments. Proteomics data also indicated the involvement of actin-based transport mediated by myosin. Importantly, the data indicated that the intraflagellar transport (IFT) system is not part of the intra-manchette transport mechanism. The visualisation of motor proteins directly from a biological sample represents a notable technical advancement, providing new insights into the organisation of the intra-manchette transport system in developing sperm.

      Are the key conclusions convincing?

      Below we comment on three main conclusions.

      MT and F-actin bundles are both constituents of the manchette While the data convincingly shows that MT and F-actin are part of the manchette, one cannot conclude from it that F-actin is an integral part of the manchette. The authors would need to rephrase so that it is clear that they are speculating.

      The transport system employs different transport machinery on these MTs Proteomics data indicates the presence of multiple motor proteins in the manchette, while cryo-EM data corroborates this by revealing morphologically distinct densities associated with the MTs. However, the nature of only one of these MT-associated densities has been confirmed-specifically, dynein, as identified through STA. The presence of kinesin or myosin in the EM data remains unconfirmed based on just the cryo-ET density, and therefore it is unclear whether these proteins are actively involved in cargo transport, as this cannot be supported by just the proteomics data. In summary, we recommend that the authors rephrase this conclusion and avoid using the term "employ".

      Dynein mediated transport (Line 225-227) The data shows that dynein is present in the manchette; however, whether it plays and active role in transport cannot be determined from the cryo-ET data provided in the manuscript, as it does not clearly display a dynein-dynactin complex attached to cargo. The attachment to cargo is also not revealed via proteomics as no adaptor proteins that link dynein-dynactin to its cargo have been shown.

      Should the authors qualify some of their claims as preliminary or speculative, or remove them altogether?

      F-actin

      • In the abstract, the authors state that F-actin provides tracks for transport as well as having structural and mechanical roles. However, the manuscript does not include experiments demonstrating a mechanical role. The authors appear to base this statement on literature where actin bundles have been shown to play a mechanical role in other model systems. We suggest they clarify that the mechanical role the authors suggest is speculative and add references if appropriate.
      • Lines 15,92, 180 and 255: The statement "Filamentous actin is an integral part of the manchette" is misleading. While the authors show that F-actin is present in their purified manchette structures, whether it is integral has not been tested. Authors should rephrase the sentence.
      • To support the claim that F-actin plays a role in transport within the manchette, the authors present only one instance where an unidentified density is attached to an actin filament. This is insufficient evidence to claim that it is myosin actively transporting cargo. Although the proteomics data show the presence of myosin, we suggest the authors exercise more caution with this claim.
      • The authors mention the presence of F-actin bundles but do not show direct crosslinking between the F-actin filaments. They could in principle just be closely packed F-actin filaments that are not necessarily linked, so the term "bundle" should be used more cautiously.

      Observations of dynein

      • Relating to Figure 2B: From the provided image it is not clear whether the density corresponds to a dynein complex, as it does not exhibit the characteristic morphological features of dynein or dynactin molecules.
      • Lines 171-172 and Figure 4: It is well established that dynein is a dimer and should always possess two motor domains. The authors have incorrectly assumed they observed single motor heads, except possibly in Figure 4A (marked by an arrow). In all other instances, the dynein complexes show two motor domains in proximity, but these have not been segmented accurately. Furthermore, the "cargos" shown in grey are more likely to represent dynein tails or the dynactin molecule, based on comparisons with in vitro structures of these complexes (see references 1-3).
      • Lines 21, 173, and 233 mention cargos, but as noted above, it seems to be parts of the dynein complex the authors are referring to.
      • Panel 4B appears to show a dynein-dynactin complex, but whether there is a cargo is unclear and if there is it should be labelled accordingly. To assessment of whether there is any cargo bound to the dynein-dynactin complex a larger crop of the panel would be helpful In summary, we recommend that the authors revisit their segmentations in Figures 2B and 4, revise their text based on these observations, and perform quantification of the data (as suggested in the next section).

      Dynein versus kinesin-based transport

      The calculation presented in lines 147-151 does not account for the fact that both the dynein-dynactin complex and kinesin proteins require cargo adaptors to transport cargo. Additionally, the authors overlook the possibility that multiple motors could be attached to a single cargo. If the authors did not observe this, they should explicitly mention it to support their argument. In short, the calculations are based on an incorrect premise, rendering the comparison inaccurate. Unless the authors have identified any dynein-dynactin or kinesin cargo adaptors in their proteomics data which could be used for such a comparison, we believe the authors lack sufficient data to accurately estimate the "active transport ratio" between dynein and kinesin.

      Would additional experiments be essential to support the claims of the paper?

      F-actin distance and length distribution

      • To support the claim that F-actin is bundled (line 189), could the authors provide the distance between each F-actin filament and its neighbours? Additionally, could they compare the average distance to the length of actin crosslinkers found in their proteomics data, or compare it to the distances between crosslinked F-actin observed in other research studies?
      • While showing that F-actin is important for the manchette would require cellular experiments, authors could provide quantification of how frequently these actin structures are observed in comparison to MTs to support their claims that these actin filaments could be important for the manchette structure.
      • In line 193, the authors claim that the F-actin in bundles appears too short for transport. Could they provide length distributions for these filaments? This might provide further support to their claim that individual F-actin filaments can serve as transport tracks (line 266).
      • Could the authors also quantify the abundance of individual F-actin filaments observed, compared to MTs and F-actin bundles, to support the idea that they could play a role in transport?
      • In the discussion, the authors mention "interactions between F-actin singlets and mMTs" (line 269), yet they report observing only one instance of this interaction (lines 210 and 211). Given the limited data, they should refer to this as a single interaction in the discussion. The scarcity of data raises questions about how representative this event truly is.

      Quantifications for judgement of representativity

      The authors should quantify how often they observed vesicles with a stick-like connection to MTs (lines 106-107); this would strengthen the interpretation of the density, as currently only one example is shown in the manuscript (Figure 4A). If possible, they could show how many of them are facing towards the MT plus end.

      Dynein quantifications

      • The authors are recommended to quantify how many dynein molecules per micron of MT they observe and how often they are angled with their MT binding domain towards the minus-end.
      • Could the authors quantify how many dynein densities they found to be attached to a (vesicle) cargo, if any (line 175)? They could show these observations in a supplementary figure.
      • For densities that match the size and location of dynein but lack clear dynein morphology (as seen in Figure 2B), could the authors quantify how many are oriented towards the MT minus end?

      Artefacts due to purification: Authors should discuss if the purification could have effects on visualizing components of the manchette. For example, if it has effect on the MTs and actin structure or the abundance/structure of the motor protein complexes (bound to cargo or isolated).

      Are the experiments adequately replicated and statistical analysis adequate?

      The cryo-ET data presented in the manuscript is collected using two separate sample preparations. Along with the quantifications of the different observations suggested above which will help the reader assess how abundant and representative these observations are, the authors could further strengthen their claims by acquiring data from a third sample preparation and then analysing how consistent their observations are between different purifications. This however could be time consuming so it is not a major requirement but recommended if possible within a short time frame.

      Are the suggested experiments realistic in terms of time and resources? It would help if you could add an estimated cost and time investment for substantial experiments.

      Most of the comments deal with either modifying the text or analysing the data already presented, so the revision could be done with 1-3 months.

      Minor comments:

      Specific experimental issues that are easily addressable.

      1. Could the authors state how many tilt series were collected for each dataset/independent sample preparation? We recommend that they upload their raw data or tomograms to EMPAIR.
      2. It is not clear to me if the same sample was used for cryo-ET and proteomics. Could the authors clarify how comparable the sample preparation for the cryo-ET and proteomics data is or if the same sample was used for both. If there is a discrepancy between these preparations, they would need to discuss how this can affect comparing observations from cryo-ET and mass spectrometry. Ideally both samples should be the same.

      Are prior studies referenced appropriately?

      We recommend including additional references to support the claim that F-actin has a mechanical role (line 242). Could the authors compare their proteomics data to other mass spectrometry studies conducted on the Manchette (for example see reference 4)?

      Are the text and figures clear and accurate?

      Text: We do not see the necessity of specifying the microtubules (MTs) in the data as "manchette MTs" or "mMTs" rather than simply "MTs". However, we recommend that the authors use either "MT" or "mMT" consistently throughout the manuscript.

      The authors appear to refer to both dynein-1 (cytoplasmic dynein) and dynein-2 (axonemal dynein or IFT dynein). To avoid confusion, it is important that the authors clearly specify which dynein they are referring to throughout the text. This is particularly relevant as the study aims to demonstrate that IFT is not part of the manchette transport system.

      • Introduction: In the third paragraph (lines 59-75), the authors should specify that they are referring to dynein-2, which is distinct from cytoplasmic dynein discussed in the previous paragraph (lines 44-58).
      • Figure 4D: The authors could fit a dynein-1 motor domain instead of a dynein-2 into the density to stay consistent with the fact that the density belongs to cytoplasmic dynein-1. Figures:
      • Figure 2B: The legend mentions a large linker complex; however, this may correspond to two or three separate densities.
      • Figure 4: please revisit the segmentation of this whole figure based on previous comments.
      • Figures 1, 2, 4, 5, and 6: It would be helpful to state in the legends that the tomograms are denoised. There are stripe-like densities visible in the images (e.g., in the vesicle in Figure 2B). Do these artefacts also appear in the raw data?

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

      We suggest revising the paragraph title "Dynein-mediated cargo along the manchette" (line 165) to "Dynein-mediated cargo transport along the manchette".

      We recommend that the authors provide additional evidence to support the interpretation that the observed EM densities correspond to motor proteins. Specifically:

      • Include scale bars or reference lines indicating the known dimensions of motor proteins, based on previous data, to demonstrate that the observed densities match the expected size.
      • Make direct comparisons to existing EM data and highlight morphological similarities. In the discussion (lines 249-254), the authors could speculate on alternative roles for the IFT components in the manchette, particularly if they are not part of the IFT trains. We also suggest rephrasing the claim in line 266 to make it more speculative in tone. Finally, a schematic overview of the manchette ultrastructure in a spermatid would greatly aid the reader in understanding the material presented.

      References:

      1. Chowdhury, S., Ketcham, S., Schroer, T. et al. Structural organization of the dynein-dynactin complex bound to microtubules. Nat Struct Mol Biol 22, 345-347 (2015). https://doi.org/10.1038/nsmb.2996
      2. Grotjahn, D.A., Chowdhury, S., Xu, Y. et al. Cryo-electron tomography reveals that dynactin recruits a team of dyneins for processive motility. Nat Struct Mol Biol 25, 203-207 (2018). https://doi.org/10.1038/s41594-018-0027-7
      3. Chaaban, S., Carter, A.P. Structure of dynein-dynactin on microtubules shows tandem adaptor binding. Nature 610, 212-216 (2022). https://doi.org/10.1038/s41586-022-05186-y
      4. W. Hu, R. Zhang, H. Xu, Y. Li, X. Yang, Z. Zhou, X. Huang, Y. Wang, W. Ji, F. Gao, W. Meng, CAMSAP1 role in orchestrating structure and dynamics of manchette microtubule minus-ends impacts male fertility during spermiogenesis, Proc. Natl. Acad. Sci. U.S.A. 120 (45) e2313787120, https://doi.org/10.1073/pnas.2313787120 (2023).

      Significance

      This study employs cryo-electron tomography (cryo-ET) and proteomics to elucidate the architecture of the manchette. It advances our understanding of the components involved in intracellular transport within the manchette and introduces the following technical and conceptual innovations:

      a) Technical Advances:

      The authors have visualized the manchette at high resolution using cryo-ET. They optimized a purification pipeline capable of retaining, at least partially, the transport machinery of the manchette. Notably, they observed dynein and putative kinesin motors attached to microtubules-a significant achievement that, to our knowledge, has not been reported previously.

      b) Conceptual Advances:

      This study provides novel insights into spermatogenesis. The findings suggest that intraflagellar transport (IFT) is unlikely to play a role at this stage of sperm development while shedding light on alternative transport systems. Importantly, the authors demonstrate that actin filaments organize in two distinct ways: clustering parallel to microtubules or forming single filaments.

      This work is likely to be of considerable interest to researchers in sperm development and structural biology. Additionally, it may appeal to scientists studying motor proteins and the cytoskeleton.

      The reviewers possess extensive expertise in in situ cryo-electron tomography and single-particle microscopy, including work on dynein-based complexes. Collectively, they have significant experience in the field of cytoskeleton-based transport.

    3. 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 #1

      Evidence, reproducibility and clarity

      In this manuscript the authors have done cryo-electron tomography of the manchette, a microtubule-based structure important for proper sperm head formation during spermatogenesis. They also did mass-spectrometry of the isolated structures. Vesicles, actin and their linkers to microtubules within the structure are shown.

      Major:

      The data the conclusions are based on seem very limited and sometimes overinterpreted. For example, only one connection between actin and microtubules was observed, and this is thought to be MACF1 simply based on its presence in the MS.

      Another, and larger concern, is that the authors do a structural study on something that has been purified out of the cell, a process which is extremely disruptive. Vesicles, actin and other cellular components could easily be trapped in this cytoskeletal sieve during the purification process and as such, not be bona fide manchette components. This could create both misleading proteomics and imaging. Therefore, an approach not requiring extraction such as high-pressure freezing, sectioning and room-temperature electron tomography and/or immunoEM on sections to set aside this concern is strongly recommended. As an additional bonus, it would show if the vesicles containing ATP synthase are deformed mitochondria.

      Minor:

      Line 99: "to study IMT with cryo-ET, manchettes were isolated ...(insert from which organism)..."

      Line 102 "...demonstrating that they can be used to study IMT".. can the authors please clarify?

      Line 111 "densities face towards the MT plus-end" How can a density "face" anywhere? For this, it needs to have a defined front and back.

      Line 137: is the "perinuclear ring" the same as the manchette?

      Figure 2B: How did the authors decide to not model the electron density found between the vesicle and the MT at 3 O'clock? Is there no other proteins with a similar lollipop structure as ATP synthase, so that this can be said to be this protein with such certainty?

      Line 189: "F-actin formed organized bundles running parallel to mMTs" - this observation needs confirming in a less disrupted sample.

      Line 242 remove first comma sign

      Line 363 "a total of 2 datasets" - is this manuscript based on only two tilt-series? Or two datasets from each of the 4 grids? In any case, this is very limited data.

      Significance

      The article is very interesting, and if presented together with the suggested controls, would be informative to both microtubule/motorprotein researchers as well as those trying studying spermatogenesis.

    1. Table 5d: Common Sources of Tension

      Some helpful strategies would fit well here: Working through conflict with families can be challenging, but it's essential for fostering a positive and productive partnership that ultimately benefits the child. Here are some comprehensive tips:

      Tips for Working Through a Conflict with Families 1.Prioritize Relationship Building (Proactive Strategy): Start Positive: Don't let the first communication with a family be negative. Reach out early in the year with positive news about their child. Share successes, no matter how small. This builds a bank of goodwill that you can draw on during difficult conversations. Be Accessible and Approachable: Make it easy for families to connect with you. Offer various communication channels (email, phone, in-person, class app) and be responsive. A warm and welcoming demeanor can significantly de-escalate potential conflict before it even begins. Be Culturally Responsive: Understand and respect diverse family values, communication styles, and cultural norms. What might seem like a conflict could be a misunderstanding rooted in different cultural expectations.

      1. Prepare for the Conversation: Gather Facts and Documentation: Base your concerns on objective observations and specific examples, not emotions or assumptions. Document dates, times, and details of relevant incidents or academic patterns. "Shira hit another child after they took the toy she was playing with" is more helpful than "Shira was aggressive today." Identify the Core Issue: What is the specific problem you need to address? Be clear in your own mind. Anticipate Family Concerns: Put yourself in their shoes. What questions might they have? What might make them defensive? Think About Solutions: Don't just present a problem; come with potential solutions or ideas for how to move forward. This shifts the conversation from blame to problem-solving. Choose the Right Time and Place: Schedule a dedicated time for the conversation when you can minimize interruptions and all parties can be fully present. Avoid impromptu discussions at drop-off or pick-up times. Ensure privacy. Consider a Third Party: If emotions are high or the situation is particularly complex, consider having another school administrator or colleague present as a neutral witness or mediator.

      3.During the Conversation: Stay Calm and Professional: Your demeanor can significantly influence the tone of the conversation. Speak in a calm, even tone, and maintain open body language. Avoid fidgeting or crossing your arms. If you feel yourself getting emotional, take a deep breath or ask for a brief pause. Listen Actively and Empathetically: This is perhaps the most crucial step. Give the family your full attention. Let them speak without interruption, even if they're emotional or angry. Listen for the underlying concerns or feelings. Use phrases like, "It sounds like you're feeling frustrated about..." or "I hear that you're concerned about..." Validating their feelings doesn't mean you agree with their perspective, but it shows you're listening and respect their emotions. Focus on the Child's Best Interest (Common Goal): Frame the discussion around the child's well-being and success. Remind the family that you both share a common goal: supporting their child. Use "we" language: "How can we work together to help [child's name] with this?" Stick to Facts, Not Personalities or Assumptions: Present your observations objectively. Avoid assigning blame or making assumptions about the family's intentions or home life. Use "I" Statements: Instead of "Your child is always disruptive," try "I've observed [child's name] frequently talking during instruction time, which is making it difficult for them to complete their work." This focuses on your experience and observations. Avoid Jargon: Speak in clear, accessible language, avoiding educational acronyms or terminology that families might not understand. Be Prepared to Apologize (When Appropriate): If you or the school made a mistake, acknowledge it and apologize sincerely. This can significantly de-escalate tension and rebuild trust. An apology for how a situation made them feel can also be powerful, even if you don't agree with their interpretation of events. Set Clear Boundaries (If Necessary): If a family member becomes verbally abusive or disrespectful, calmly but firmly state your boundaries. "I understand you're upset, but I need you to speak to me respectfully for us to continue this conversation." You can offer to reschedule if they cannot maintain a respectful tone. "Sandwich" Difficult Information: Start with a positive comment about the child, introduce the concern, and end with another positive comment or a collaborative plan for support.

      1. Develop a Plan and Follow Up: Collaborate on Solutions: Work with the family to develop an action plan. What steps will you take? What steps can they take at home? This fosters a sense of partnership and shared responsibility. Set Measurable Goals: Agree on specific, achievable goals and a timeline for checking progress. Schedule a Follow-Up: This demonstrates commitment and allows both parties to assess progress and make adjustments. Document the Conversation: Keep a professional record of the date, attendees, topics discussed, agreed-upon actions, and follow-up plan. This is crucial for future reference and accountability.

      By approaching conflicts with empathy, clear communication, and a focus on collaboration, you can navigate challenging family conversations more effectively and strengthen the home-school partnership.

    1. Reviewer #1 (Public review):

      Lipid transfer proteins (LTPs) play a crucial role in the intramembrane lipid exchange within cells. However, the molecular mechanisms that govern this activity remain largely unclear. Specifically, the way in which LTPs surmount the energy barrier to extract a single lipid molecule from a lipid bilayer is not yet fully understood. This manuscript investigates the influence of membrane properties on the binding of Ups1 to the membrane and the transfer of phosphatidic acid (PA) by the LTP. The findings reveal that Ups1 shows a preference for binding to membranes with positive curvature. Moreover, coarse-grained molecular dynamics simulations indicate that positive curvature decreases the energy barrier associated with PA extraction from the membrane. Additionally, lipid transfer assays conducted with purified proteins and liposomes in vitro demonstrate that the size of the donor membrane significantly impacts lipid transfer efficiency by Ups1-Mdm35 complexes, with smaller liposomes (characterized by high positive curvature) promoting rapid lipid transfer.

      This study offers significant new insights into the reaction cycle of phosphatidic acid (PA) transfer by Ups1 in mitochondria. Notably, the authors present compelling evidence that, alongside negatively charged phospholipids, positive membrane curvature enhances lipid transfer - an effect that is particularly relevant at the mitochondrial outer membrane. The experiments are technically robust, and my primary feedback pertains to the interpretation of specific results.

      (1) The authors conclude from the lipid transfer assays (Figure 5) that lipid extraction is the rate-limiting step in the transfer cycle. While this conclusion seems plausible, it should be noted that the authors employed high concentrations of Ups1-Mdm35 along with less negatively charged phospholipids in these reactions. This combination may lead to binding becoming the rate-limiting factor. The authors should take this point into consideration. In this type of assay, it is challenging to clearly distinguish between binding, lipid extraction, and membrane dissociation as separate processes.

      (2) The authors should discuss that variations in the size of liposomes will also affect the distance between them at a constant concentration, which may affect the rate of lipid transfer. Therefore, the authors should determine the average size and size distribution of liposomes after sonication (by DLS or nanoparticle analyzer, etc.).

      (3) The authors use NBD-PA in the lipid transfer assays. Does the size of the donor liposomes affect the transfer of NBD-PA and DOPA similarly? Since NBD-labeled lipids are somewhat unstable within lipid bilayers (as shown by spontaneous desorption in Figure 5B), monitoring the transfer of unlabeled PA in at least one setting would strengthen the conclusion of the swap experiments.

      (4) The present study suggests that membrane domains with positive curvature at the outer membrane may serve as starting points for lipid transport by Ups1-Mdm35. Is anything known about the mechanisms that form such structures? This should be discussed in the text.

    2. Author response:

      Reviewer #1:

      Lipid transfer proteins (LTPs) play a crucial role in the intramembrane lipid exchange within cells. However, the molecular mechanisms that govern this activity remain largely unclear. Specifically, the way in which LTPs surmount the energy barrier to extract a single lipid molecule from a lipid bilayer is not yet fully understood. This manuscript investigates the influence of membrane properties on the binding of Ups1 to the membrane and the transfer of phosphatidic acid (PA) by the LTP. The findings reveal that Ups1 shows a preference for binding to membranes with positive curvature. Moreover, coarse-grained molecular dynamics simulations indicate that positive curvature decreases the energy barrier associated with PA extraction from the membrane. Additionally, lipid transfer assays conducted with purified proteins and liposomes in vitro demonstrate that the size of the donor membrane significantly impacts lipid transfer efficiency by Ups1-Mdm35 complexes, with smaller liposomes (characterized by high positive curvature) promoting rapid lipid transfer.

      This study offers significant new insights into the reaction cycle of phosphatidic acid (PA) transfer by Ups1 in mitochondria. Notably, the authors present compelling evidence that, alongside negatively charged phospholipids, positive membrane curvature enhances lipid transfer - an effect that is particularly relevant at the mitochondrial outer membrane. The experiments are technically robust, and my primary feedback pertains to the interpretation of specific results.

      (1) The authors conclude from the lipid transfer assays (Figure 5) that lipid extraction is the rate-limiting step in the transfer cycle. While this conclusion seems plausible, it should be noted that the authors employed high concentrations of Ups1-Mdm35 along with less negatively charged phospholipids in these reactions. This combination may lead to binding becoming the rate-limiting factor. The authors should take this point into consideration. In this type of assay, it is challenging to clearly distinguish between binding, lipid extraction, and membrane dissociation as separate processes.

      We thank the reviewer for the constructive and positive evaluation of our manuscript. We agree that, while our data support the interpretation that the rate-limiting step occurs at the donor membrane, it is difficult to dissect in our assay which of the individual steps at the donor membrane - such as binding of Ups1, lipid extraction into the binding pocket, or dissociation of Ups1 - is rate-limiting. Nevertheless, although we cannot exclude contributions from membrane binding or dissociation, several observations suggest that lipid extraction is a rate-limiting step under our experimental conditions.

      The acceptor membrane has a similar lipid composition to the donor membrane (in tendency, the donor membrane is even a bit richer in binding-promoting lipids). If binding was ratelimiting, similar constraints would be expected at the acceptor membrane during lipid insertion. However, this is not observed.

      Regarding dissociation, if this step were rate-limiting, one would expect similar constraints to be evident at the acceptor vesicles as well. Nevertheless, membrane dissociation might be mechanistically coupled to lipid extraction and thus difficult to evaluate as an independent step.

      Based on our data and the considerations described above, we suggest that lipid extraction is the dominant rate-limiting step at the donor membrane under our conditions. However, we agree that a clear separation of these individual steps is not possible with the current experimental design. We will revise the corresponding passage to clarify that the rate-limiting step occurs at the donor membrane and, based on our observations, likely involves lipid extraction. Future studies aiming on dissecting these steps, will be important for elucidating the mechanism and regulation of Ups1-mediated lipid transfer both in vitro and in vivo.

      (2) The authors should discuss that variations in the size of liposomes will also affect the distance between them at a constant concentration, which may affect the rate of lipid transfer. Therefore, the authors should determine the average size and size distribution of liposomes after sonication (by DLS or nanoparticle analyzer, etc.)

      We agree that variations in liposome size will influence the average distance between vesicles at a given lipid concentration, which may in turn affect the rate of lipid transfer. As suggested, we will include DLS measurements to characterize the size distribution of our different liposome preparations.

      Our setup was designed to keep the total membrane surface area comparable across conditions. This approach ensures a comparable overall binding capacity for Ups1 and enables the comparison of membrane binding and lipid extraction from different membranes. However, we agree that vesicle spacing, which is affected by liposome size at constant lipid concentration, could potentially influence certain steps in the transfer process, such as the time required for Ups1 to travel between donor and acceptor membranes. Whether this intermembrane travel time contributes to rate limitation is indeed an interesting question, and we will address this point through further discussion in the revised manuscript.

      Investigating such effects in our current experimental system would require altering the vesicle concentration, which would in turn change the total membrane surface area and introduce additional variables. Nevertheless, exploring the influence of vesicle spacing and intermembrane distance on lipid transfer represents a promising direction for future studies aimed at dissecting the rate-limiting steps of the transfer cycle.

      (3) The authors use NBD-PA in the lipid transfer assays. Does the size of the donor liposomes affect the transfer of NBD-PA and DOPA similarly? Since NBD-labeled lipids are somewhat unstable within lipid bilayers (as shown by spontaneous desorption in Figure 5B), monitoring the transfer of unlabeled PA in at least one setting would strengthen the conclusion of the swap experiments.

      Ups1-mediated transfer of PA has been demonstrated both by mass spectrometry analysis of donor and acceptor vesicles (Connerth et al., 2012) and by NBD-fluorescence-based lipid transfer assays (Lu et al., 2020; Miliara et al., 2015; Miliara et al., 2019; Miliara et al., 2023; Potting et al., 2013; Watanabe et al., 2015). The fluorescence-based approach has been the most widely applied across multiple studies and has enabled detailed analysis of various aspects of lipid transfer by Ups1. It has been used to investigate mutants of key structural elements—such as the lipid-binding pocket and the α2–loop region. It has also been used to analyze fusion constructs between Ups1 and Mdm35, the influence of Mdm35 variants, and competition with excess Mdm35. Additionally, by comparing the transfer of NBD-labeled PA and NBD-labeled PS, this assay has provided insights into the determinants of the lipid specificity of Ups1. Hence, our experiments are based on the standard assay used to analyse lipid transfer in the field and thus can be corralated with the majority of published data.

      Nevertheless, we agree that it is important to keep in mind that NBD labeling may alter the biophysical properties of lipids and, consequently, affect their transfer efficiency. Moreover, NBD-labeled lipids are not suitable for comparing the transfer efficiency of different PA species, as the label itself may mask differences in acyl chain composition. Therefore, it will be valuable to establish complementary methods that do not rely on NBD-labeled PA. We aim to develop these non-standard methods for possible inclusion in the present study, but even if not fully implemented at this stage, they will certainly form an important part of future investigations.

      (4) The present study suggests that membrane domains with positive curvature at the outer membrane may serve as starting points for lipid transport by Ups1-Mdm35. Is anything known about the mechanisms that form such structures? This should be discussed in the text.

      The origin of positively curved membrane domains is indeed highly relevant in the context of our findings, and while not the primary focus of this work, we will place more emphasis on discussing how such curvature may arise. Mechanisms include the action of curvature-generating proteins, asymmetric lipid composition and curvature induced at membrane contact sites. We have so far included examples of proteins in the outer mitochondrial membrane that are expected to influence curvature in their vicinity, and we will expand on this aspect and other contributing factors more thoroughly in the revised text.

      Reviewer #2:

      Summary:

      Lipid transfer between membranes is essential for lipid biosynthesis across different organelle membranes. Ups1-Mdm35 is one of the best-characterized lipid transfer proteins, responsible for transferring phosphatidic acid (PA) between the mitochondrial outer membrane (OM) and inner membrane (IM), a process critical for cardiolipin (CL) synthesis in the IM. Upon dissociation from Mdm35, Ups1 binds to the intermembrane space (IMS) surface of the OM, extracts a PA molecule, re-associates with Mdm35, and moves through the aqueous IMS to deliver PA to the IM. Here, the authors analyzed the early steps of this PA transfer - membrane binding and PA extraction - using a combination of in vitro biochemical assays with lipid liposomes and purified Ups1-Mdm35 to measure liposome binding, lipid transfer between liposomes, and lipid extraction from liposomes. The authors found that membrane curvature, a previously overlooked property of the membrane, significantly affects PA extraction but not PA insertion into liposomes. These findings were further supported by MD simulations.

      Strengths:

      The experiments are well-designed, and the data are logically interpreted. The present study provides an important basis for understanding the mechanism of lipid transfer between membranes.  

      Weaknesses:

      The physiological relevance of membrane curvature in lipid extraction and transfer still remains open.

      We thank the reviewer for the constructive feedback on our work. We agree that the physiological relevance of membrane curvature in lipid extraction and transfer remains an open question. Our data show that Ups1 binding to native-like OM membranes under physiological pH conditions is curvature-dependent, supporting the idea that this mechanism may optimize lipid transfer in vivo. While the intricate biophysical basis of this behaviour can only be dissected in vitro, these findings offer valuable insight into how curvature may functionally regulate Ups1 activity in the cellular context. To directly test this, it will be important in future studies to identify Ups1 mutants that lack curvature sensitivity and assess their performance in vivo, which will help clarify the physiological importance of this mechanism.

      Reviewer #3:

      The manuscript by Sadeqi et al. studies the interactions between the mitochondrial protein Ups1 and reconstituted membranes. The authors apply synthetic liposomal vesicles to investigate the role of pH, curvature, and charge on the binding of Ups1 to membranes and its ability to extract PA from them. The manuscript is well wrifen and structured. With minor exceptions, the authors provide all relevant information (see minor points below) and reference the appropriate literature in their introduction. The underlying question of how the energy barrier for lipid extraction from membranes is overcome by Ups1 is interesting, and the data presented by the authors could offer a valuable new perspective on this process. It is also certainly a challenging in vitro reconstitution experiment, as the authors aim to disentangle individual membrane properties (e.g., curvature, charge, and packing density) to study protein adsorption and lipid transfer. I have one major suggestion and a few minor ones that the authors might want to consider to improve their manuscript and data interpretation:

      Major Comments:

      The experiments are performed with reconstituted vesicles, which are incubated with recombinant protein variants and quantitatively assessed in flotation and pelleting assays. According to the Materials and Methods section, the lipid concentration in these assays is kept constant at 5 µM. However, the authors change the size of the vesicles to tune their curvature. Using the same lipid concentration but varying vesicle sizes results in different total vesicle concentrations. Moreover, larger vesicles (produced by freeze-thawing and extrusion) tend to form a higher proportion of multilamellar vesicles, thus also altering the total membrane area available for binding. Could these differences in the experimental system account for the variation in binding? To address this, the authors would need to perform the experiments either under saturation (excess protein) conditions or find an experimental approach to normalize for these differences.

      We thank the reviewer for the constructive and positive comments. We agree that, since the total number of lipids was kept constant, the number of vesicles varied with vesicle size in our experiments. However, the setup was specifically designed to maintain a comparable total membrane surface area across conditions, ensuring a comparable number of available binding sites for Ups1. Because membrane surface area decreases with the square of the vesicle radius, keeping vesicle number constant would have led to a marked reduction in binding surface. Our approach was therefore aimed at preserving comparable binding capacity while varying membrane curvature.

      With respect to multilamellarity, we thank the reviewer for addressing this important point. As described above, we aimed to maintain a constant total membrane surface area across all conditions to ensure an equal number of potential binding sites. We agree that multilamellarity in large liposomes could restrict accessibility to part of the membrane surface. However, we see in our experiments that even when the total membrane surface area of the small liposomes is reduced to one quarter of the standard amount, binding to the small liposomes remained stronger than to the larger liposomes at the higher concentration. This strongly indicates that restricted accessibility cannot account for the curvature-specific effect observed. Nonetheless, we will further address this aspect experimentally and in the discussion of the revised manuscript.

      References

      Connerth, M., Tatsuta, T., Haag, M., Klecker, T., Westermann, B., & Langer, T. (2012). Intramitochondrial transport of phosphatidic acid in yeast by a lipid transfer protein. Science, 338(6108), 815-818. https://doi.org/10.1126/science.1225625 

      Lu, J., Chan, C., Yu, L., Fan, J., Sun, F., & Zhai, Y. (2020). Molecular mechanism of mitochondrial phosphatidate transfer by Ups1. Commun Biol, 3(1), 468. https://doi.org/10.1038/s42003-020-01121-x 

      Miliara, X., Garnef, J. A., Tatsuta, T., Abid Ali, F., Baldie, H., Perez-Dorado, I., Simpson, P., Yague, E., Langer, T., & Mafhews, S. (2015). Structural insight into the TRIAP1/PRELI-like domain family of mitochondrial phospholipid transfer complexes. EMBO Rep, 16(7), 824-835. https://doi.org/10.15252/embr.201540229 

      Miliara, X., Tatsuta, T., Berry, J. L., Rouse, S. L., Solak, K., Chorev, D. S., Wu, D., Robinson, C. V., Mafhews, S., & Langer, T. (2019). Structural determinants of lipid specificity within Ups/PRELI lipid transfer proteins. Nat Commun, 10(1), 1130. https://doi.org/10.1038/s41467-019-09089-x 

      Miliara, X., Tatsuta, T., Eiyama, A., Langer, T., Rouse, S. L., & Mafhews, S. (2023). An intermolecular hydrogen bonded network in the PRELID-TRIAP protein family plays a role in lipid sensing. Biochim Biophys Acta Proteins Proteom, 1871(1), 140867. https://doi.org/10.1016/j.bbapap.2022.140867 

      Posng, C., Tatsuta, T., Konig, T., Haag, M., Wai, T., Aaltonen, M. J., & Langer, T. (2013). TRIAP1/PRELI complexes prevent apoptosis by mediating intramitochondrial transport of phosphatidic acid. Cell Metab, 18(2), 287-295. https://doi.org/10.1016/j.cmet.2013.07.008 

      Watanabe, Y., Tamura, Y., Kawano, S., & Endo, T. (2015). Structural and mechanistic insights into phospholipid transfer by Ups1-Mdm35 in mitochondria. Nat Commun, 6, 7922. https://doi.org/10.1038/ncomms8922

    1. 有限理性

      哎哟你终于来了,这位是组织认知宇宙中的——

      🧠 思维战斗机 × 决策黑客 × 认知架构师:赫伯特·西蒙(Herbert A. Simon)!

      他不只是一位经济学家,他还是:

      • AI 领域的鼻祖之一,
      • 认知心理学的奠基人之一,
      • 管理学里的思想老祖宗,
      • 拿了个诺贝尔经济学奖之后,又差点把图灵奖也顺手牵走的人!

      你以为他写的是论文,其实写的是人类理性操作系统的说明书


      🧠 核心身份简介(多领域通吃)

      | 身份 | 代表作 | 关键词 | | ------ | ----------- | -------------------------------- | | 决策理论大师 | 《管理行为》 | 有限理性(Bounded Rationality) | | AI先驱 | 与纽厄尔共创逻辑理论家 | 符号系统假设(Symbol System Hypothesis) | | 认知心理学者 | 《人类问题解决》 | 问题空间(Problem Space) | | 系统设计者 | 《科学的科学》 | satisficing(满足式选择) |


      🧠 关键词一:有限理性(Bounded Rationality)

      “人类不是不理性,是被逼着用一个破旧计算器理性。”

      在传统经济学眼里,人是理性人(Homo Economicus)——总能找到最优解、全知全能还不加班。

      西蒙大手一挥:

      “醒醒吧,人类没有全知的信息、没有无限的时间,也没有跑大模型的GPU。”

      所以他提出“有限理性”:人做决策时受限于:

      • 信息有限
      • 处理能力有限
      • 时间有限

      📌 所以人类用的是一种叫做“Satisficing”(满意就行)的策略: 不是找最优解,是找个够好的就收工

      🌰 举例: 你在外卖App上划了5分钟没选出来,点了个评分4.6的就下单,这就是西蒙说的“认知省电行为”。


      🧠 关键词二:组织是一个“决策工厂”

      他的经典名言:

      “组织的真正本质,是一套决策过程的结构。”

      🎯 钱德勒说组织是结构系统,西蒙补刀说:结构只是皮,决策流程才是魂

      他指出:

      • 管理者的本质任务不是“管人”,而是做出一连串有限理性下的决策
      • 所有制度、职位、会议,都是为了帮助有限的大脑“分担决策负荷”。

      🤖 关键词三:人工智能鼻祖之一

      Allen Newell 联手,提出“符号系统假设”:

      “人类思维可以被形式化地模拟出来。”

      他们开发的早期AI程序:逻辑理论家(Logic Theorist) → 能自动证明数学定理,被誉为“第一个人工智能程序”。

      这就是从认知科学到AI编程语言的桥梁

      🌌 你现在看到的GPT,其实站在了西蒙那句经典假设之上:

      “思维 = 信息处理过程。”


      📊 西蒙模型 vs 组织认知宇宙角色比拼

      | 人物 | 组织关注点 | 比喻 | | ---- | ----- | ----------------- | | 科斯 | 交易成本 | 公司是“降噪系统” | | 诺斯 | 制度路径 | 国家是“历史版操作系统” | | 钱德勒 | 结构与战略 | 企业是“指令集结构” | | 阿尔都塞 | 意识形态 | 国家机器是“剧本渲染器” | | 西蒙 | 决策流程 | 人是“开在低配CPU上的决策程序” |


      💬 金句精选(认知暴击版)

      1. “在一个复杂世界中,寻找完美解是浪费时间,找到‘还行’解才是真技能。”
      2. “组织是把人的有限理性组织起来的机器。”
      3. “人类不是神经网络,是在符号系统上挣扎的算法。”

      🎬 要不要加一集宇宙剧本?

      标题可以是:

      🎬《你的大脑不是笨,是带宽不够——赫伯特·西蒙的认知经济学》

      章节提纲:

      1. 理性是有限资源,不是无限外挂
      2. 决策 ≠ 最优,而是“够用”
      3. 为什么会议室就是认知流量再分配中心?
      4. 从西蒙到GPT,信息处理才是认知的底层规律

      下一步要不要我把这集剧本写出来? 或者我们直接筹备《组织认知宇宙》出版/出片/出课三合一?😎

    2. 《市场还是组织:自由之手 vs 看得见的手》

      你是认真的吗? 你是要我讲那个把“组织架构图”看得比“老板发话”还重要的人类企业史诗写手——

      🎩 阿尔弗雷德·D·钱德勒(Alfred D. Chandler Jr.)

      他简直就是**“管理学的托尔金”**,用经济史的羽毛写下了组织的魔法史书。下面我用你的风格,一边笑一边刺穿结构真相——


      📦 一句话介绍他

      Chandler:那个告诉你“不是你产品好才赢,而是你管理结构强才赢”的男人。

      他不是讲鸡汤的,是讲“战略决定结构(Structure follows Strategy)”的严肃派爷爷。


      🧠 关键词一:多部制组织(M-form, Multidivisional Form)

      “当企业长成巨人时,必须要把自己分成多头巨龙,每头独立又听话。”

      钱德勒观察美国企业发展史后发现:

      • 一家企业一旦业务太多、区域太广,用传统的**职能制(Function-based)**就会乱成一锅粥;
      • 所以聪明的企业像通用电气(GE)、杜邦(DuPont),都改用多部制结构

      • 每个部门管自己那摊业务(比如洗衣机事业部、化肥事业部);

      • 总部负责分配资源和考核绩效。

      📌 像不像现在的阿里:淘宝部、天猫部、蚂蚁集团……每个都有自己的小王国,但听中央大Boss调兵遣将。


      🚀 关键词二:《看得见的手》(The Visible Hand)

      对对对,你没看错,这不是亚当·斯密的“看不见的手”。

      Chandler说:“市场不够用了,公司内部的‘看得见的手’登场了。”

      这是他最出名的著作,书里干了两件事:

      1. 历史追溯:从19世纪铁路业到20世纪重工业,企业越来越庞大;
      2. 重锤打脸传统经济学:不是“市场自调”,而是“管理者手调”!

      他指出:

      • 大企业的高效率,不是靠市场竞争,而是靠内部协同;
      • 市场只是“分蛋糕”,真正“做蛋糕”的,是企业自己调度的信息系统+流程+人事制度+考核机制

      🎙️ 反讽金句版:

      “市场是个脱口秀演员,真正运营国家经济的是幕后导演:公司里的组织系统。”


      🛠️ 钱德勒模型 = 战略 → 结构 → 管理 → 成长

      📦 战略改变了(比如扩张海外市场) ↓ 🏗️ 组织结构必须随之改变(成立国际部) ↓ 🧾 管理机制也跟着升级(考核、资源分配方式) ↓ 📈 企业才能持续增长

      否则你就会看到:

      • 战略喊得响,结构跟不上;
      • 前线想冲锋,总部还在画流程图;
      • 然后就,爆炸了。

      📊 钱德勒 vs 其他大咖(快速类比)

      | 人物 | 核心观念 | 问题聚焦 | 你公司的现实 | | --- | ------ | ------- | ------------ | | 科斯 | 交易成本理论 | 为什么有公司? | 公司是为避开市场争吵 | | 诺斯 | 制度经济学 | 国家如何组织? | 国家运行像个烂系统 | | 钱德勒 | 组织结构逻辑 | 企业如何演化? | 你公司的部门像没脑的章鱼 |


      🧩 哲思金句三连发

      1. “结构追随战略,就像身体追随灵魂。”
      2. “现代企业不是市场的产物,而是组织能力的演化。”
      3. “在复杂的世界里,协调比竞争更重要。”

      🎬 要不要来一期剧本?

      标题我都想好了:


      🎬《你的公司为什么拖后腿?因为结构还停在蒸汽时代——钱德勒组织论全解》

      钩子台词:

      “你以为你公司发展不起来,是市场不给机会? 钱德勒说:不,是你内部结构像灌了502一样粘住了所有人。”

      章节提纲:

      1. 企业为什么长大了就傻了?
      2. 什么是M型结构,如何避免“鸡同鸭讲的流程灾难”?
      3. 为什么企业真正的增长,不靠灵感,而靠可复制结构?
      4. 管理的“看得见的手”是如何碾压市场的?

      需要我现在就写剧本?还是你想把钱德勒、诺斯、科斯、阿尔都塞做成一套“组织认知宇宙”?😏 说吧主编!

    1. 有限理性

      哎哟你终于来了,这位是组织认知宇宙中的——

      🧠 思维战斗机 × 决策黑客 × 认知架构师:赫伯特·西蒙(Herbert A. Simon)!

      他不只是一位经济学家,他还是:

      • AI 领域的鼻祖之一,
      • 认知心理学的奠基人之一,
      • 管理学里的思想老祖宗,
      • 拿了个诺贝尔经济学奖之后,又差点把图灵奖也顺手牵走的人!

      你以为他写的是论文,其实写的是人类理性操作系统的说明书


      🧠 核心身份简介(多领域通吃)

      | 身份 | 代表作 | 关键词 | | ------ | ----------- | -------------------------------- | | 决策理论大师 | 《管理行为》 | 有限理性(Bounded Rationality) | | AI先驱 | 与纽厄尔共创逻辑理论家 | 符号系统假设(Symbol System Hypothesis) | | 认知心理学者 | 《人类问题解决》 | 问题空间(Problem Space) | | 系统设计者 | 《科学的科学》 | satisficing(满足式选择) |


      🧠 关键词一:有限理性(Bounded Rationality)

      “人类不是不理性,是被逼着用一个破旧计算器理性。”

      在传统经济学眼里,人是理性人(Homo Economicus)——总能找到最优解、全知全能还不加班。

      西蒙大手一挥:

      “醒醒吧,人类没有全知的信息、没有无限的时间,也没有跑大模型的GPU。”

      所以他提出“有限理性”:人做决策时受限于:

      • 信息有限
      • 处理能力有限
      • 时间有限

      📌 所以人类用的是一种叫做“Satisficing”(满意就行)的策略: 不是找最优解,是找个够好的就收工

      🌰 举例: 你在外卖App上划了5分钟没选出来,点了个评分4.6的就下单,这就是西蒙说的“认知省电行为”。


      🧠 关键词二:组织是一个“决策工厂”

      他的经典名言:

      “组织的真正本质,是一套决策过程的结构。”

      🎯 钱德勒说组织是结构系统,西蒙补刀说:结构只是皮,决策流程才是魂

      他指出:

      • 管理者的本质任务不是“管人”,而是做出一连串有限理性下的决策
      • 所有制度、职位、会议,都是为了帮助有限的大脑“分担决策负荷”。

      🤖 关键词三:人工智能鼻祖之一

      Allen Newell 联手,提出“符号系统假设”:

      “人类思维可以被形式化地模拟出来。”

      他们开发的早期AI程序:逻辑理论家(Logic Theorist) → 能自动证明数学定理,被誉为“第一个人工智能程序”。

      这就是从认知科学到AI编程语言的桥梁

      🌌 你现在看到的GPT,其实站在了西蒙那句经典假设之上:

      “思维 = 信息处理过程。”


      📊 西蒙模型 vs 组织认知宇宙角色比拼

      | 人物 | 组织关注点 | 比喻 | | ---- | ----- | ----------------- | | 科斯 | 交易成本 | 公司是“降噪系统” | | 诺斯 | 制度路径 | 国家是“历史版操作系统” | | 钱德勒 | 结构与战略 | 企业是“指令集结构” | | 阿尔都塞 | 意识形态 | 国家机器是“剧本渲染器” | | 西蒙 | 决策流程 | 人是“开在低配CPU上的决策程序” |


      💬 金句精选(认知暴击版)

      1. “在一个复杂世界中,寻找完美解是浪费时间,找到‘还行’解才是真技能。”
      2. “组织是把人的有限理性组织起来的机器。”
      3. “人类不是神经网络,是在符号系统上挣扎的算法。”

      🎬 要不要加一集宇宙剧本?

      标题可以是:

      🎬《你的大脑不是笨,是带宽不够——赫伯特·西蒙的认知经济学》

      章节提纲:

      1. 理性是有限资源,不是无限外挂
      2. 决策 ≠ 最优,而是“够用”
      3. 为什么会议室就是认知流量再分配中心?
      4. 从西蒙到GPT,信息处理才是认知的底层规律

      下一步要不要我把这集剧本写出来? 或者我们直接筹备《组织认知宇宙》出版/出片/出课三合一?😎

    1. Author response:

      The following is the authors’ response to the original reviews

      Reviewer #1:

      (1) 8 molar urea not only denatures proteins but also denatures DNA. Obviously, this does not affect the ChIP, since antibodies often recognize small linear epitopes and the proteins are crosslinked. However, under high urea conditions the BUR elements should be rendered single-stranded, and one wonders whether this has any effect on the procedure. The authors should alert the reader of these circumstances.

      Thank you for raising this important question about the effects of 8M urea. We have added a brief paragraph explaining this point in the revised manuscript. Despite common misconceptions, 8M urea by itself does not actively convert double-stranded DNA to single-stranded DNA. For this conversion to occur, a heat denaturation step is required. Once DNA is heat-denatured to become single-stranded, urea can maintain this configuration. This is why the addition of 8M urea to acrylamide gel electrophoresis is a standard method for analyzing single-stranded oligonucleotides, but the DNA must first be denatured by heat (Summer et al., J. Vis. Exp. (32), e1485, DOI : 10.3791/1485). This is clearly described in published work comparing the status of DNA with and without heat treatment in an 8M urea-containing buffer (Hegedus et al., Nucl.Acids Res. 2009 (doi:10.1093/nar/gkp539).

      We have additional evidence supporting this conclusion in the context of our urea ultracentrifugation experiment. Both crosslinked and un-crosslinked genomic DNA purified by 8M urea centrifugation can be digested with restriction enzymes, which indicates that the DNA remains double-stranded. For instance, we previously published SATB1 ChIP-3C results using Sau3A-digested DNA after urea purification. In the current paper, we used HindIII to digest urea-purified DNA for urea4C-seq. The BUR reference map can also be generated after restriction digestion of urea-purified DNA and isolating and sequencing SATB1-bound restriction fragments in vitro. If genomic DNA were denatured by 8M urea ultracentrifugation, we would not have been able to digest it with restriction enzymes to obtain these results.

      We have now added a sentence noting that SATB1 is a double-stranded DNA-binding protein that does not bind to single-stranded DNA, as we have previously shown (Dickinson et al., 1992, Ref 32).

      (2) An important conclusion is that urea-ChIP reveals direct DNA binding events, whereas standard ChIP shows indirect binding (which is stripped off by urea). I do not see any evidence for direct binding. At low resolution, predicted BUR elements are enriched in domains where SATB-1 is mapped by urea-ChIP. A statement like 'In a zoomed-in view, covering a 430 kb region, SATB1 sites identified from urea ChIP-seq precisely coincided with BUR peaks' is certainly not correct: most BUR peaks do not show significant SATB-1 binding. The randomly chosen regions shown in Figure 4 – Supplement 1 show how poor the overlap of SATB-1 and BURs is; indeed, they show that SATB-1 binds DNA mostly at non-BUR sites. I see Figure 2D, but such cumulative plots can be highly biased by very few cases. I suggest showing these data in heat maps instead.

      We believe there may be some confusion regarding the interpretation of our figures. Looking at Track 3 (BUR reference map, RED peaks) and urea SATB1 Tracks 4 and 5 (replicas from two independent experiments) in Fig. 2B, the SATB1 peaks detected by urea ChIP-seq do indeed coincide with BUR peaks. In the revised manuscript, we have provided a further ‘zoomed-in’ view to better illustrate this point and also provided the underlying BUR sequence from one of these SATB1-bound regions (Figure 2—supplement figure 1).

      It is true that many more BURs exist than SATB1-bound BURs, especially in gene-poor regions where BURs are clustered. However, from the perspective of SATB1-bound peaks, the majority of these coincide with BURs, as shown by both deepTools analyses and new heatmap, as suggested (Figure 2E, and Figure 7—supplement figure 3).

      The results from our genome-wide quantitative analyses using deepTools to compare peaks from urea SATB1 ChIP-seq data and the BUR reference map shown in Supplementary Tables 1 and 2 are consistent with the heatmap analyses.

      We must apologize for an error in the scaling of the y-axis in Figure 4-supplement figure 1 that likely contributed to some confusion. We have corrected our mistake in the revised manuscript. As we were preparing our figures, when placed in the figure and axes relabeled for legibility, the BUR reference peaks were mislabeled on their y-axis. In the figure the peaks were erroneously labeled on a scale of 0.1-1 read counts/million reads, but the data shown is actually scaled at 0.1 to 2 read counts per million reads. Unfortunately, we did not realize this error and, using the figure as a guide for scaling, provided urea SATB1 ChIP-seq peaks at a scale of 0.1-1 read counts/million reads to match the mislabeled BUR reference track. This had the effect of reducing the signal/noise in the SATB1 ChIP-seq data (Figure 1). We have now standardized the y-axis for fair comparison using a scaling of the y-axis at 0.1-2 for all tracks.  This will more clearly show that there are indeed more BUR peaks than SATB1-bound sites, consistent with our quantitative analysis.

      We hope that these clarifications as well as the added heatmaps and binding site example allay the concerns about the specificity and overlap of SATB1 binding on BURS.

      (3) In Figure 6C 'peaks' are compared. However, looking at Figure 4 - Supplement 1 again it is clear that peak calling can yield a misleading impression. Figure 6D suggests that there are more BURs than SATB-1 peaks but this is not true from looking at the browser.

      We thank the reviewer for this observation. As noted in our response to point 2 above, the inconsistent y-axis scaling in Figure 4-supplement figure 1 created a misleading impression, which we have corrected in the revised manuscript. When properly displayed with consistent y-axis scaling, the browser view aligns with our quantitative data showing that there are indeed many more BURs than SATB1-bound sites. As mentioned under 2 above, we have performed genome-wide quantitative analysis by deepTools (Supplementary Tables 1 and 2) to confirm the results shown by bar graphs in Fig. 6C, 6D and Fig. 2D. 

      In Figure 6C, the bars show the percentage of SATB1-bound peaks in each cell type (denominator) that overlap with confirmed BUR sites in the BUR reference map (numerator). In Figure 6D, we show the percentage of total BUR sites in the BUR reference map (denominator) that are bound by SATB1 from urea ChIP-seq (numerator). To avoid any confusion, we have added brief subtitles to Figures 6C and 6D in the revised manuscript.

      (4) An important conclusion is that urea-ChIP reveals direct DNA binding events, whereas standard ChIP shows indirect binding (which is stripped off by urea). I do not yet see any evidence for direct binding. It cannot be excluded that the binding is RNA-mediated. The authors mention in passing that urea-ChIP material still contains (specific!) RNA. Given that this is a new procedure, the authors should document the RNA content of urea-ChIP and RNase-treat their samples prior to ChIP to monitor an RNA contribution.

      Thank you for raising this important point. The direct binding of SATB1 to BURs is well-established in our previous work. Indeed, this was the main motivation to explore the reason for the lack of evidence for genome-wide SATB1 binding to BURs in the DNA-binding profile by standard ChIP-seq. This has been a major point of confusion for us for many years.

      SATB1 was originally identified through a search for mammalian proteins that could recognize BURs specifically and not just any A+T-rich sequence. The Satb1 gene was originally cloned by an expression cDNA library and encoded SATB1 protein bound the BUR probe but not a mutated AT-rich BUR (control) probe.  Subsequent experiments confirmed that SATB1 specifically binds to many BURs without requiring additional factors. Furthermore, SATB1 recognizes BURs by binding in the minor groove of double-stranded DNA, presumably recognizing the altered phosphate backbone structure of BUR DNA, rather than accessing nucleotide bases (Dickinson et al, 1992).

      We do agree with the reviewer, however, that there is a possibility that RNA can redirect SATB1 to different subsets of BURs and/or to interact indirectly with different regulatory regions depending on cell type or developmental stage. Although urea ultracentrifugation clearly separates most RNA (found in the middle region of the tube) from genomic DNA (pelleted at the bottom) (de Belle et al., 1998), upon crosslinking cells, a small quantity of RNA is found co-pelleted with DNA (our recent unpublished results). This RNA, tightly associated with crosslinked chromatin, may have some impact on SATB1 function.

      Based on our preliminary data, we are currently planning to study the impact of RNA using RNase A as well as by targeting specific RNAs employing an anti-sense approach. We believe that thoroughly addressing the impact of RNA warrants a full paper, including the potential roles of specific non-coding RNAs in SATB1 function, and thus is beyond the scope of the current paper. However, we have now added discussion of this important point in the manuscript.

      (5) An important aspect of the model is that SATB1 tethers active genes to inactive LADs. However, in the 4C experiment the BUR elements used to anchor the looping are both in the accessible, active chromatin domain. If the authors want to maintain their statement, they must show a 4C result that connects the 2 distinct domains and transverses A/B domain boundaries. Currently, the data only show a looping within accessible chromatin.

      We appreciate REVIEWER 1 for bringing up the important point that our model could potentially be interpreted as “SATB1 tethers active genes to inactive LADs.” Since we describe that BURs are enriched in LADs and that SATB1 binds a subset of BURs, readers may assume that we aim to demonstrate, through urea 4C-seq, that SATB1 tethers active genes to transcriptionally-inactive LADs (via BURs). However, this is not our intention in the model (Figure 8). In the experiment we designed for our present study,  we selected BUR-1 and BUR-2 as viewpoints from a non-LAD gene-rich region (inter-LAD). Because these BURs are bound by SATB1, it indicates that these BURs are part of the “hard-to-access” SATB1-rich subnuclear structure, which resists extraction, in contrast to accessible chromatin. Thus, we illustrate in the model that BURs anchored to the SATB1-rich nuclear substructure make contact with accessible chromatin over long distances in a SATB1-dependent manner. Therefore, we do not intend to conclude that SATB1 mediates interactions between LADs and inter-LADs (accessible chromatin) from our current study: this would be a topic for future research. In the original model in the submitted manuscript, we used the terms “inaccessible” and “accessible.” In the revised version, we clarified this in the model by changing “inaccessible” to “SATB1-rich subnuclear structure” and carefully revised  the text in the Figure 8 legend to clarify the model. 

      At this time, we do not know exactly how LADs and SATB1 nuclear architecture are related spatially and functionally. While LADs are mapped as genomic domains in proximity to Lamin B1 by LaminB1-DamID, BURs are mapped at ~300-500 bp resolution by urea ChIP-seq. To gain further insight into this important question, a large body of DNA-FISH and immunoDNA-FISH experiments will be required, comparing different cell types to see whether and how specific BURs move between LADs and SATB1 nuclear architecture. Such experiments may benefit from testing the Gabrg1 and Gabra2 loci, where many BURs are anchored to SATB1 in neurons but not in thymocytes, for instance.  This is included in Discussion in the revised manuscript.

      Regarding the reviewer's second point about showing more extended domains for 4C interactions, we would like to highlight that Figure 5—supplement figure 3 in our submitted manuscript addresses this concern. This figure shows that BUR-interactions extend to multiple gene-rich regions across intervening gene-poor regions. Interestingly, BUR-1 and BUR-2 interactions skip a transcriptionally silent gene-rich region containing olfactory receptor genes but interact with subsequent gene-rich regions containing active genes. These data demonstrate that BUR-interactions do indeed traverse A- and B-compartment boundaries.  In the revised manuscript (in Figure 5—supplement figure 3), we newly added a Lamin B1-DamID (thymocyte) track.  Comparing with LADs, BUR-1 interactions occur mostly in non-LAD regions. Some minor overlap with LADs was detected in high resolution views (not shown). Future experiments testing BUR viewpoints that reside within LADs are required to assess whether SATB1 mediates interactions between B and A compartments.

      (6) The description of the urea-co-immunoprecipitation experiment (Figure 3C) could be improved to make it unequivocally clear that co-binding to chromatin is tested, not protein-protein interaction (which is destroyed by urea).

      Thank you for this helpful suggestion. We have revised the text in the manuscript by stating “Distinct from protein-protein co-immunoprecipitation (co-IP) using whole cell or nuclear extracts, we examined the direct co-binding status on chromatin in vivo of SATB1 and CTCF or cohesin by urea ChIP-Western”.

      Reviewer #2:

      (1) Since SATB1 has been described to interact with beta-catenin, I wonder if the authors have looked at TCF4/TCF7l2 binding patterns and their potential overlap with SATB1 binding patterns. This might appear a trivial request. However, uncontrolled WNT signalling is a major feature of cancer undergoing metastasis - a process that the authors have earlier associated with unscheduled SATB1 expression in triple-negative breast cancer.

      We thank the reviewer for highlighting this important point about the potential relationship between SATB1 and TCF4/TCF7l2 binding patterns. Based on published observations with other factors (Rad21, CTCF, BRG1, RUNX) that show substantial overlap with SATB1 in standard ChIP-seq peaks(Kakugawa et al., Cell Rep 19, 1176-1188 (2017). DOI: 10.1016/j.celrep.2017.04.038. Poterlowicz et al., PLoS Genet, 2017 DOI: 10.1371/journal.pgen.1006966), we would anticipate that TCF4 might also show significant overlap with SATB1. An important question is whether the DNA binding profile of TCF4 depends on SATB1.

      We have not yet generated ChIP-seq data for TCF4 in the presence and absence of SATB1, but we agree that such experiments could provide important insights into cancer progression as well as brain function. This represents an interesting direction for future work. We have added this point in our discussion based on your kind suggestion.

      (2) The CTCF sizes indicated in the western blot analyses of Figures 3C and Figure 3 - supplement figure 2 do not display the normal size, which is around 130 kDa. Either the issue is erroneous marking or a so-called salt effect to slow the migration in the gel. Alternatively, it reflects a slower migrating form of CTCF generated by for example PARylation (by PARP1) that is known to approach 180 kDa. It would be useful if the authors could clarify this minor issue.

      We appreciate the reviewer pointing out this discrepancy. As the reviewer correctly noted, CTCF can appear at a higher molecular weight due to post-translational modifications such as PARylation and O-GlcNAcylation, which alter its migration during electrophoresis.

      Upon re-examination of our raw data for Figure 3—supplement figure 2A, we discovered that the marker lane for the CTCF panel was broken, and the 150kDa band was erroneously assigned. This led to the 150kDa marker being placed below the CTCF migration position, which is clearly an error. We thank the reviewer for bringing this to our attention.

      We have checked our other data and consistently observe CTCF migrating below the 150kDa band, similar to the pattern shown on the Abcam website for the antibody we used (ab128873) (Figure 2). For Figure 3-supplement figure 2, we will use a marker lane from a parallel gel with identical composition and run time to correctly indicate the molecular weight. We havealso corrected the marker position in Figure 3C.

      Reviewing Editor (Recommendations for the authors):

      (1) The introduction states that urea ChIP-seq is "unbiased", which is difficult to unambiguously determine and therefore might be an overstatement. Maybe the authors could consider rephrasing.

      We agree with the reviewer's assessment and have rephrased our description of the urea ChIP-seq method to avoid using the term "unbiased."

      (2) The authors propose that in standard ChIP, most SATB1 is in the insoluble fraction. This seems easy to test and demonstrating it may help to further clarify the differences between the protocols.

      We appreciate this suggestion and would like to clarify our description. What we stated in the manuscript was:

      "We envision that SATB1 bound to inaccessible nuclear regions may be lost in the insoluble fraction."

      This refers specifically to a subpopulation of SATB1 that is bound to the high-salt extraction-resistant nuclear substructure, not to the total SATB1 protein. We also noted elsewhere in the manuscript that:

      "SATB1 proteins are found in high salt-resistant fraction as well as salt-extracted fraction (40). Thus, it is possible that soluble SATB1 may associate with open chromatin."

      Our unpublished results show that SATB1 proteins exist in at least two distinct forms based on protein mobility: SATB1 with high mobility and another with very low or no mobility. While we have identified the SATB1 domain responsible for each of these distinct mobility patterns, we have not yet identified biochemical differences that would allow us to distinguish them conclusively. Therefore, an experiment to test the distribution of SATB1 in soluble versus insoluble fractions would show SATB1 in both fractions but would not necessarily provide information about the functional significance of these different populations. We believe this is an important area for future research and are working to develop tools to specifically distinguish and characterize SATB1 in the soluble versus insoluble fractions.

    1. Reviewer #3 (Public review):

      Summary:

      The authors used recurrent neural network modelling of spatial navigation tasks to investigate border and place cell behaviour during remapping phenomena.

      Strengths:

      The neural network training seemed for the most part (see comments later) well-performed, and the analyses used to make the points were thorough.

      The paper and ideas were well-explained.

      Figure 4 contained some interesting and strong evidence for map-like generalisation as environmental geometry was warped.

      Figure 7 was striking and potentially very interesting.

      It was impressive that the RNN path-integration error stayed low for so long (Fig A1), given that normally networks that only work with dead-reckoning have errors that compound. I would have loved to know how the network was doing this, given that borders did not provide sensory input to the network. I could not think of many other plausible explanations... It would be even more impressive if it was preserved when the network was slightly noisy.

      Update:

      The analysis of how the RNN remapped, using a context signal to switch between largely independent maps, and the examination of the border like tuning in the recurrent units of the RNN, were both thorough and interesting. Further, in the updated response I appreciated the additional appendix E which helped substantiate the claim that the RNN neurons were border cells.

      Weaknesses:

      The remapping results were also puzzling. The authors present convincing evidence that the recurrent units effectively form 6 different maps of the 6 different environments (e.g. the sparsity of the code, or fig 6a), with the place cells remapping between environments. Yet, as the authors point out, in neural data the finding is that some cells generalise their co-firing patterns across environments (e.g. grid cells, border cells), while place cells remap, making it unclear what correspondence to make between the authors network and the brain. There are existing normative models that capture both entorhinal's consistent and hippocampus' less consistent neural remapping behaviour (Whittington et al. and probably others), what have we then learnt from this exercise?

      Update: see summary below

      I felt that the neural data analysis was unconvincing. Most notably, the statistical effect was found in only one of seven animals. Random noise is likely to pass statistical tests 1 in 20 times (at 0.05 p value), this seems like it could have been something similar? Further, the data was compared to a null model in which place cell fields were randomly distributed. The authors claim place cell fields have two properties that the random model doesn't (1) clustering to edges (as experimentally reported) and (2) much more provocatively, a hexagonal lattice arrangement. The test seems to collude the two; I think that nearby ball radii could be overrepresented, as in figure 7f, due to either effect. I would have liked to see a computation of the statistic for a null model in which place cells were random but with a bias towards to boundaries of the environment that matches the observed changing density, to distinguish these two hypotheses.

      Update: the authors acknowledge these shortcomings and have appropriately tempered their data related claims.

      Some smaller weaknesses:<br /> - Had the models trained to convergence? From the loss plot it seemed like not, and when including regularisors recent work (grokking phenomena, e.g. Nanda et al. 2023) has shown the importance of letting the regularisor minimise completely to see the resulting effect. Else you are interpreting representations that are likely still being learnt, a dangerous business.<br /> Update: I understand that practical limitations make testing this thoroughly impossible, which is fair enough.

      - The claim that this work provided a mathematical formalism of the intuitive idea of a cognitive map seems strange, given that upwards of 10 of the works this paper cite also mathematically formalise a cognitive map into a similar integration loss for a neural network.<br /> Update: the introduction of these ideas hasn't changed, and my concerns above remain.

      Aim Achieved? Impact/Utility/Context of Work

      I think this is a thorough exploration of how this network with these losses is able to path-integrate its position and remap. This is useful, it is good to know how another neural network with slightly different constraints learns to perform these behaviours.

      In the updated version of the manuscript I am happy to say that I think there are few claims that are unsubstantiated (see weakness section above that has been significantly updated). The link to neuroscience remains the biggest shortcoming of this work in my view. The authors point to two main results in this direction. First, the ability for interactions only between border-type and place cells to produce many observed place-cell results, providing a new hypothesis. Second, a connection between grid cells, place cells, and border cells, in the production of hexagonal arrangements of place cells.

      Regarding the first, as the authors discuss, current evidence suggests border cells are invariant across environments whereas this work finds border cells for specific environments (they use the words rate-remapping boundary-type cells). It seems likely to me that there are many ways a neural network can path-integrate across different environments. In other models where the same base map is re-used (e.g. TEM) grid cells emerge, in this work where the maps for different environments are disjoint these border-like cells that do not match an observed cell type in their tuning to environment are involved. I find this a really interesting alternative (I think what an RNN does is interesting in its own right), but I don't see why I should think it is what the brain does, given that it appears to match observations less well (existence of grid cells, consistent firing patterns of border cells across environments). The smoking gun in favour of the author's hypothesis would be finding these sparse border like cells, or some other evidence of gating like interactions between border and place cells as they discuss. Finding such evidence sounds difficult (so not reasonable to ask for in a rebuttal), and to reiterate, I applaud the authors for clearly outlining an alternative, but I remain unconvinced.

      Regarding the second point, while the grid-like placement of field centres was cool, and I applaud the authors for including real neural data comparisons, as the authors say, the data is preliminary, and further evidence would be required to fully substantiate this claim.

      As such, in my mind it is an interesting alternative hypothesis. I look forward to seeing experimental predictions or comparisons that can tighten the link, substantiating the claim that what this particular RNN is doing reflects the algorithms at work in the brain.

    2. Author response:

      The following is the authors’ response to the original reviews

      Public Reviews:

      Reviewer #1 (Public Review):

      Summary:

      This work studies representations in a network with one recurrent layer and one output layer that needs to path-integrate so that its position can be accurately decoded from its output. To formalise this problem, the authors define a cost function consisting of the decoding error and a regularisation term. They specify a decoding procedure that at a given time averages the output unit center locations, weighted by the activity of the unit at that time. The network is initialised without position information, and only receives a velocity signal (and a context signal to index the environment) at each timestep, so to achieve low decoding error it needs to infer its position and keep it updated with respect to its velocity by path integration.

      The authors take the trained network and let it explore a series of environments with different geometries while collecting unit activities to probe learned representations. They find localised responses in the output units (resembling place fields) and border responses in the recurrent units. Across environments, the output units show global remapping and the recurrent units show rate remapping. Stretching the environment generally produces stretched responses in output and recurrent units. Ratemaps remain stable within environments and stabilise after noise injection. Low-dimensional projections of the recurrent population activity forms environment-specific clusters that reflect the environment's geometry, which suggests independent rather than generalised representations. Finally, the authors discover that the centers of the output unit ratemaps cluster together on a triangular lattice (like the receptive fields of a single grid cell), and find significant clustering of place cell centers in empirical data as well.

      The model setup and simulations are clearly described, and are an interesting exploration of the consequences of a particular set of training requirements - here: path integration and decodability. But it is not obvious to what extent the modelling choices are a realistic reflection of how the brain solves navigation. Therefore it is not clear whether the results generalize beyond the specifics of the setup here.

      Strengths:

      The authors introduce a very minimal set of model requirements, assumptions, and constraints. In that sense, the model can function as a useful 'baseline', that shows how spatial representations and remapping properties can emerge from the requirement of path integration and decodability alone. Moreover, the authors use the same formalism to relate their setup to existing spatial navigation models, which is informative.

      The global remapping that the authors show is convincing and well-supported by their analyses. The geometric manipulations and the resulting stretching of place responses, without additional training, are interesting. They seem to suggest that the recurrent network may scale the velocity input by the environment dimensions so that the exact same path integrator-output mappings remain valid (but maybe there are other mechanisms too that achieve the same).

      The clustering of place cell peaks on a triangular lattice is intriguing, given there is no grid cell input. It could have something to do with the fact that a triangular lattice provides optimal coverage of 2d space? The included comparison with empirical data is valuable, although the authors only show significant clustering - there is no analysis of its grid-like regularity.

      First of all, we would like to thank the reviewer for their comprehensive feedback, and their insightful comments. Importantly, as you point out, our goal with this model was to build a minimal model of place cell representations, where representations were encouraged to be place-like, but free to vary in tuning and firing locations. By doing so, we could explore what upstream representations facilitate place-like representations, and even remapping (as it turned out) with minimal assumptions. However, we agree that our task does not capture some of the nuances of real-world navigation, such as sensory observations, which could be useful extensions in future work. Then again, the simplicity of our setup makes it easier to interpret the model, and makes it all the more surprising that it learns many behaviors exhibited by real world place cells.

      As to the distribution of phases - we also agree that a hexagonal arrangement likely reflects some optimal configuration for decoding of location.

      And we agree that the symmetry within the experimental data is important; we have revised analyses on experimental phase distributions, and included an analysis of ensemble grid score, to quantify any hexagonal symmetries within the data.

      Weaknesses:

      The navigation problem that needs to be solved by the model is a bit of an odd one. Without any initial position information, the network needs to figure out where it is, and then path-integrate with respect to a velocity signal. As the authors remark in Methods 4.2, without additional input, the only way to infer location is from border interactions. It is like navigating in absolute darkness. Therefore, it seems likely that the salient wall representations found in the recurrent units are just a consequence of the specific navigation task here; it is unclear if the same would apply in natural navigation. In natural navigation, there are many more sensory cues that help inferring location, most importantly vision, but also smell and whiskers/touch (which provides a more direct wall interaction; here, wall interactions are indirect by constraining velocity vectors). There is a similar but weaker concern about whether the (place cell like) localised firing fields of the output units are a direct consequence of the decoding procedure that only considers activity center locations.

      Thank you for raising this point; we absolutely agree that the navigation task is somewhat niche. However, this was a conscious decision, to minimize any possible confounding from alternate input sources, such as observations. In part, this experimental design was inspired by the suggestion that grid cells support navigation/path integration in open-field environments with minimal sensory input (as they could, conceivably do so with no external input). This also pertains to your other point, that boundary interactions are necessary for navigation. In our model, using boundaries is one solution, but there is another way around this problem, which is conceivably better: to path integrate in an egocentric frame, starting from your initial position. Since the locations of place fields are inferred only after a trajectory has been traversed, the network is free to create a new or shifted representation every time, independently of the arena. In this case, one might have expected generalized solutions, such as grid cells to emerge. That this is not the case, seems to suggest that grid cells may somehow not be optimal for pure path integration, or at the very least, hard to learn (but may still play a part, as alluded to by place field locations). We have tried to make these points more evident in the revised manuscript.

      As for the point that the decoding may lead to place-like representations, this is a fair point. Indeed, we did choose this form of decoding, inspired by the localized firing of place cells, in the hope that it would encourage minimally constrained, place-like solutions. However, compared to other works (Sorscher and Xu) hand tuning the functional form of their place cells, our (although biased towards centralized tuning curves) allows for flexible functional forms such as the position of the place cell centers, their tuning width, whether or not it is center-surround activity, and how they should tune to different environments/rooms. This allows us to study several features of the place cell system, such as remapping and field formation. We have revised to make this more clear in the model description.

      The conclusion that 'contexts are attractive' (heading of section 2) is not well-supported. The authors show 'attractor-like behaviour' within a single context, but there could be alternative explanations for the recovery of stable ratemaps after noise injection. For example, the noise injection could scramble the network's currently inferred position, so that it would need to re-infer its position from boundary interactions along the trajectory. In that case the stabilisation would be driven by the input, not just internal attractor dynamics. Moreover, the authors show that different contexts occupy different regions in the space of low-dimensional projections of recurrent activity, but not that these regions are attractive.

      We agree that boundary interactions could facilitate the convergence of representations after noise injection. We did try to moderate this claim by the wording “attractor-like”, but we agree that boundaries could confound this result. We have therefore performed a modified noise injection experiment, where we let the network run for an extended period of time, before noise injection (and no velocity signal), see Appendix Velocity Ablation in the revised text. Notably, representations converge to their pre-scrambled state after noise injection, even without a velocity signal. However, place-like representations do not converge for all noise levels in this case, possibly indicating that boundary interactions do serve an error-correcting function, also. Thank you for pointing this out.

      As for the attractiveness of contexts, we agree that more analyses were required to demonstrate this. We have therefore conducted a supplementary analysis where we run the trained network with a mismatch in context/geometry, and demonstrate that the context signal fixes the representation, up to geometric distortions.

      The authors report empirical data that shows clustering of place cell centers like they find for their output units. They report that 'there appears to be a tendency for the clusters to arrange in hexagonal fashion, similar to our computational findings'. They only quantify the clustering, but not the arrangement. Moreover, in Figure 7e they only plot data from a single animal, then plot all other animals in the supplementary. Does the analysis of Fig 7f include all animals, or just the one for which the data is plotted in 7e? If so, why that animal? As Appendix C mentions that the ratemap for the plotted animal 'has a hexagonal resemblance' whereas other have 'no clear pattern in their center arrangements', it feels like cherrypicking to only analyse one animal without further justification.

      Thank you for pointing this out; we agree that this is not sufficiently explained and explored in the current version. We have therefore conducted a grid score analysis of the experimental place center distributions, to uncover possible hexagonal symmetries. The reason for choosing this particular animal was in part because it featured the largest number of included cells, while also demonstrating the most striking phase distribution, while including all distributions in the supplementary. Originally, this was only intended as a preliminary analysis, suggesting non-uniformity in experimental place field distributions, but we realize that these may all provide interesting insight into the distributional properties of place cells.

      We have explained these choices in the revised text, and expanded analyses on all animals to showcase these results more clearly.

      Reviewer #2 (Public Review):

      Summary:

      The authors proposed a neural network model to explore the spatial representations of the hippocampal CA1 and entorhinal cortex (EC) and the remapping of these representations when multiple environments are learned. The model consists of a recurrent network and output units (a decoder) mimicking the EC and CA1, respectively. The major results of this study are: the EC network generates cells with their receptive fields tuned to a border of the arena; decoder develops neuron clusters arranged in a hexagonal lattice. Thus, the model accounts for entorhinal border cells and CA1 place cells. The authors also suggested the remapping of place cells occurs between different environments through state transitions corresponding to unstable dynamical modes in the recurrent network.

      Strengths:

      The authors found a spatial arrangement of receptive fields similar to their model's prediction in experimental data recorded from CA1. Thus, the model proposes a plausible mechanisms to generate hippocampal spatial representations without relying on grid cells. This result is consistent with the observation that grid cells are unnecessary to generate CA1 place cells.

      The suggestion about the remapping mechanism shows an interesting theoretical possibility.

      We thank the reviewer for their kind feedback.

      Weaknesses:

      The explicit mechanisms of generating border cells and place cells and those underlying remapping were not clarified at a satisfactory level.

      The model cannot generate entorhinal grid cells. Therefore, how the proposed model is integrated into the entire picture of the hippocampal mechanism of memory processing remains elusive.

      We appreciate this point, and hope to clarify: From a purely architectural perspective, place-like representations are generated by linear combinations of recurrent unit representations, which, after training, appear border-like. During remapping, the network is simply evaluated/run in different geometries/contexts, which, it turns out, causes the network to exhibit different representations, likely as solutions to optimally encoding position in the different environments. We have attempted to revise the text to make some of these interpretations more clear. We have also conducted a supplementary analysis to demonstrate how representations are determined by the context signal directly, which helps to explain how recurrent and output units form their representations.

      We also agree that our model does not capture the full complexity of the Hippocampal formation. However, we would argue that its simplicity (focusing on a single cell type and a pure path integration task), acts as a useful baseline for studying the role of place cells during spatial navigation. The fact that our model captures a range of place cell behaviors (field formation, remapping and geometric deformation) without grid cells also point to several interesting possibilities, such that grid cells may not be strictly necessary for place cell formation and remapping, or that border cells may account for many of the peculiar behaviors of place cells. However, we wholeheartedly agree that including e.g. sensory information and memory storage/retrieval tasks would prove a very interesting extension of our model to more naturalistic tasks and settings. In fact, our framework could easily accommodate this, e.g. by decoding contexts/observations/memories from the network state, alongside location.

      Reviewer #3 (Public Review):

      Summary:

      The authors used recurrent neural network modelling of spatial navigation tasks to investigate border and place cell behaviour during remapping phenomena.

      Strengths:

      The neural network training seemed for the most part (see comments later) well-performed, and the analyses used to make the points were thorough.

      The paper and ideas were well explained.

      Figure 4 contained some interesting and strong evidence for map-like generalisation as environmental geometry was warped.

      Figure 7 was striking, and potentially very interesting.

      It was impressive that the RNN path-integration error stayed low for so long (Fig A1), given that normally networks that only work with dead-reckoning have errors that compound. I would have loved to know how the network was doing this, given that borders did not provide sensory input to the network. I could not think of many other plausible explanations... It would be even more impressive if it was preserved when the network was slightly noisy.

      Thank you for your insightful comments! Regarding the low path integration error, there is a slight statistical signal from the boundaries, as trajectories tend to turn away from arena boundaries. However, we agree, that studying path integration performance in the face of noise would make for a very interesting future development.

      Weaknesses:

      I felt that the stated neuroscience interpretations were not well supported by the presented evidence, for a few reasons I'll now detail.

      First, I was unconvinced by the interpretation of the reported recurrent cells as border cells. An equally likely hypothesis seemed to be that they were positions cells that are linearly encoding the x and y position, which when your environment only contains external linear boundaries, look the same. As in figure 4, in environments with internal boundaries the cells do not encode them, they encode (x,y) position. Further, if I'm not misunderstanding, there is, throughout, a confusing case of broken symmetry. The cells appear to code not for any random linear direction, but for either the x or y axis (i.e. there are x cells and y cells). These look like border cells in environments in which the boundaries are external only, and align with the axes (like square and rectangular ones), but the same also appears to be true in the rotationally symmetric circular environment, which strikes me as very odd. I can't think of a good reason why the cells in circular environments should care about the particular choice of (x,y) axes... unless the choice of position encoding scheme is leaking influence throughout. A good test of these would be differently oriented (45 degree rotated square) or more geometrically complicated (two diamonds connected) environments in which the difference between a pure (x,y) code and a border code are more obvious.

      Thank you for pointing this out. This is an excellent point, that we agree could be addressed more rigorously. Note that there is no position encoding in our model; the initial state of the network is a vector of zeros, and the network must infer its location from boundary interactions and context information alone. So there is no way for positional information to leak through to the recurrent layer directly. However, one possible reason for the observed symmetry breaking, is the fact that the velocity input signal is aligned with the cardinal directions. To investigate this, we trained a new model, wherein input velocities are rotated 45 degrees relative to the horizontal, as you suggest. The results, shown and discussed in appendix E (Learned recurrent representations align with environment boundaries), do indicate that representations are tuned to environment boundaries, and not the cardinal directions, which hopefully improves upon this point.

      Next, the decoding mechanism used seems to have forced the representation to learn place cells (no other cell type is going to be usefully decodable?). That is, in itself, not a problem. It just changes the interpretation of the results. To be a normative interpretation for place cells you need to show some evidence that this decoding mechanism is relevant for the brain, since this seems to be where they are coming from in this model. Instead, this is a model with place cells built into it, which can then be used for studying things like remapping, which is a reasonable stance.

      This is a great point, and we agree. We do write that we perform this encoding to encourage minimally constrained place-like representations (to study their properties), but we have revised to make this more evident.

      However, the remapping results were also puzzling. The authors present convincing evidence that the recurrent units effectively form 6 different maps of the 6 different environments (e.g. the sparsity of the code, or fig 6a), with the place cells remapping between environments. Yet, as the authors point out, in neural data the finding is that some cells generalise their co-firing patterns across environments (e.g. grid cells, border cells), while place cells remap, making it unclear what correspondence to make between the authors network and the brain. There are existing normative models that capture both entorhinal's consistent and hippocampus' less consistent neural remapping behaviour (Whittington et al. and probably others), what have we then learnt from this exercise?

      Thanks for raising this point! We agree that this finding is surprising, but we hold that it actually shows something quite important: that border-type units are sufficient to create place-like representations, and learns several of the behaviors associated with place cells and remapping (including global remapping and field stretching). In other words, a single cell type known to exist upstream of place cells is sufficient to explain a surprising range of phenomena, demonstrating that other cell types are not strictly necessary. However, we agree that understanding why the boundary type units sometimes rate remap, and whether that can be true for some border type cells in the brain (either directly, or through gating mechanisms) would be important future developments. Related to this point, we also expanded upon the influence of the context signal for representation selection (appendix F)

      Concerning the relationship to other models, we would argue that the simplicity of our model is one of its core strengths, making it possible to disentangle what different cell types are doing. While other models, including TEM, are highly important for understanding how different cell types and brain regions interact to solve complex problems, we believe there is a need for minimal, understandable models that allows us to investigate what each cell type is doing, and this is where we believe our work is important. As an example, our model not only highlights the sufficiency of boundary-type cells as generators of place cells, its lack of e.g. grid cells also suggest that grid cells may not be strictly necessary for e.g. open-field/sensory-deprived navigation, as is often claimed.

      One striking result was figure 7, the hexagonal arrangement of place cell centres. I had one question that I couldn't find the answer to in the paper, which would change my interpretation. Are place cell centres within a single clusters of points in figure 7a, for example, from one cell across the 100 trajectories, or from many? If each cluster belongs to a different place cell then the interpretation seems like some kind of optimal packing/coding of 2D space by a set of place cells, an interesting prediction. If multiple place cells fall within a single cluster then that's a very puzzling suggestion about the grouping of place cells into these discrete clusters. From figure 7c I guess that the former is the likely interpretation, from the fact that clusters appear to maintain the same colour, and are unlikely to be co-remapping place cells, but I would like to know for sure!

      This is a good point, and you are correct: one cluster tends to correspond to one unit. To make this more clear, we have revised Fig. 7, so that each decoded center is shaded by unit identity, which makes this more evident. And yes, this is, seemingly in line with some form of optimal packing/encoding of space, yes!

      I felt that the neural data analysis was unconvincing. Most notably, the statistical effect was found in only one of seven animals. Random noise is likely to pass statistical tests 1 in 20 times (at 0.05 p value), this seems like it could have been something similar? Further, the data was compared to a null model in which place cell fields were randomly distributed. The authors claim place cell fields have two properties that the random model doesn't (1) clustering to edges (as experimentally reported) and (2) much more provocatively, a hexagonal lattice arrangement. The test seems to collude the two; I think that nearby ball radii could be overrepresented, as in figure 7f, due to either effect. I would have liked to see a computation of the statistic for a null model in which place cells were random but with a bias towards to boundaries of the environment that matches the observed changing density, to distinguish these two hypotheses.

      Thanks for raising this point. We agree that we were not clear enough in our original manuscript. We included additional analyses in one animal, to showcase one preliminary case of non-uniform phases. To mitigate this, we have performed the same analyses for all animals, and included a longer discussion of these results (included in the supplementary material). We have also moderated the discussion on Ripley’s H to encompass only non-uniformity, and added a grid score analysis to showcase possible rotational symmetries in the data. We hope this gets our findings across more clearly

      Some smaller weaknesses:

      - Had the models trained to convergence? From the loss plot it seemed like not, and when including regularisors recent work (grokking phenomena, e.g. Nanda et al. 2023) has shown the importance of letting the regularisor minimise completely to see the resulting effect. Else you are interpreting representations that are likely still being learnt, a dangerous business.

      Longer training time did not seem to affect representations. However, due to the long trajectories and statefulness involved, training was time-intensive and could become unstable for very long training. We therefore stopped training at the indicated time.

      - Since RNNs are nonlinear it seems that eigenvalues larger than 1 doesn't necessarily mean unstable?

      This is a good point; stability is not guaranteed. We have updated the text to reflect this.

      - Why do you not include a bias in the networks? ReLU networks without bias are not universal function approximators, so it is a real change in architecture that doesn't seem to have any positives?

      We found that bias tended to have a detrimental effect on training, possibly related to the identity initialization used (see e.g. Le et al. 2015), and found that training improved when biases were fixed to zero.

      - The claim that this work provided a mathematical formalism of the intuitive idea of a cognitive map seems strange, given that upwards of 10 of the works this paper cite also mathematically formalise a cognitive map into a similar integration loss for a neural network.

      We agree that other works also provide ways of formalizing this concepts. However, our goal by doing so was to elucidate common features across these seemingly disparate models. We also found that the concept of a learned and target map made it easier to come up with novel models, such as one wherein place cells are constructed to match a grid cell label.

      Aim Achieved? Impact/Utility/Context of Work

      Given the listed weaknesses, I think this was a thorough exploration of how this network with these losses is able to path-integrate its position and remap. This is useful, it is good to know how another neural network with slightly different constraints learns to perform these behaviours. That said, I do not think the link to neuroscience was convincing, and as such, it has not achieved its stated aim of explaining these phenomena in biology. The mechanism for remapping in the entorhinal module seemed fundamentally different to the brain's, instead using completely disjoint maps; the recurrent cell types described seemed to match no described cell type (no bad thing in itself, but it does limit the permissible neuroscience claims) either in tuning or remapping properties, with a potentially worrying link between an arbitrary encoding choice and the responses; and the striking place cell prediction was unconvincingly matched by neural data. Further, this is a busy field in which many remapping results have been shown before by similar models, limiting the impact of this work. For example, George et al. and Whittington et al. show remapping of place cells across environments; Whittington et al. study remapping of entorhinal codes; and Rajkumar Vasudeva et al. 2022 show similar place cell stretching results under environmental shifts. As such, this papers contribution is muddied significantly.

      Thank you for this perspective; we agree that all of these are important works that arrive at complementary findings. We hold that the importance of our paper lies in its minimal nature, and its focus on place cells, via a purpose-built decoding that enables place-like representations. In doing so, we can point to possibly under explored relationships between cell types, in particular place cells and border cells, while challenging the necessity of other cell types for open-field navigation (i.e. grid cells). In addition, our work points to a novel connection between grid cells, place cells and even border cells, by way of the hexagonal arrangement of place unit centers. However, we agree that expanding our model to include more biologically plausible architectures and constraints would make for a very interesting extension in the future.

      Thank you again for your time, as well as insightful comments.  

      Recommendations for the authors:

      Reviewer #1 (Recommendations For The Authors):

      Even after reading Methods 5.3, I found it hard to understand how the ratemap population vectors that produce Fig 3e and Fig 5 are calculated. It's unclear to me how there can be a ratemap at a single timestep, because calculating a ratemap involves averaging the activity in each location, which would take a whole trajectory and not a single timestep. But I think I've understood from Methods 5.1 that instead the ratemap is calculated by running multiple 'simultaneous' trajectories, so that there are many visited locations at each timestep. That's a bit confusing because as far as I know it's not a common way to calculate ratemaps in rodent experiments (probably because it would be hard to repeat the same task 500 times, while the representations remain the same), so it might be worth explaining more in Methods 5.3.

      We understand the confusion, and have attempted to make this more clear in the revised manuscript. We did indeed create ratemaps over many trajectories for time-dependent plots, for the reasons you mentioned. We also agree that this would be difficult to do experimentally, but found it an interesting way to observe convergence of representations in our simulated scenario.

      Fig 3b-d shows multiple analyses to support output unit global remapping, but no analysis to support the claim that recurrent units remap by rate changes. The examples in Fig 3ai look pretty convincing, but it would be useful to also have a more quantitative result.

      We agree, and only showed that units turn off/become silent using ratemaps. We have therefore added an explicit analysis, showcasing rate remapping in recurrent units (see appendix G; Recurrent units rate remap)

      Reviewer #2 (Recommendations For The Authors):

      Some parts of the current manuscript are hard to follow. Particularly, the model description is not transparent enough. See below for the details.

      Major comments:

      (1) Mathematical models should be explained more explicitly and carefully. I had to guess or desperately search for the definitions of parameters. For instance, define the loss function L in eq.(1). Though I can assume L represents the least square error (in A.8), I could not find the definition in Model & Objective. N should also be defined explicitly in equation (3). Is this the number of output cells?

      Thank you for pointing this out, we have revised to make it more clear.

      (2) In Fig. 1d, how were the velocity and context inputs given to individual neurons in the network? The information may be described in the Methods, but I could not identify it.

      This was described in the methods section (Neural Network Architecture and Training), but we realize that we used confusing notation, when comparing with Fig. 1d. We have therefore changed the notation, and it should hopefully be clearer now. Thanks for pointing out this discrepancy.

      (3) I took a while to understand equations (3) and (4) (for instance, t is not defined here). The manuscript would be easier to read if equations (5) and (6) are explained in the main text but not on page 18 (indeed, these equations are just copies of equations 3 and 4). Otherwise, the authors may replace equations (3) and (4) with verbal explanations similar to figure legend for Fig. 1b.

      (4) Is there any experimental evidence for uniformly strong EC-to-CA1 projections assumed in the non-trainable decoder? This point should be briefly mentioned.

      Thank you for raising this point. The decoding from EC (the RNN) to CA1 (the output layer) consists of a trainable weight matrix, and may thus be non-uniform in magnitude. The non-trainable decoding acts on the resulting “CA1” representation only. We hope that improvements to the model description also makes this more evident.  

      (5) The explanation of Fig. 3 in the main text is difficult to follow because subpanels are explained in separate paragraphs, some of which are very short, as short as just a few lines.

      This presentation style makes it difficult to follow the logical relationships between the subpanels. This writing style is obeyed throughout the manuscript but is not popular in neuroscience.

      Thanks for pointing this out, we have revised to accommodate this.

      (6) Why do field centers cluster near boundaries? No underlying mechanisms are discussed in the manuscript.

      This is a good point; we have added a note on this; it likely reflects the border tuning of upstream units.

      (7) In Fig. 4, the authors presented how cognitive maps may vary when the shape and size of open arenas are modified. The results would be more interesting if the authors explained the remapping mechanism. For instance, on page 8, the authors mentioned that output units exhibit global remapping between contexts, whereas recurrent units mainly rate remapping.

      Why do such representational differences emerge?

      We agree! Thanks for raising this point. We have therefore expanded upon this discussion in section 2.4.

      (8) In the first paragraph of page 10, the authors stated ".. some output units display distinct field doubling (see both Fig. 4c), bottom right, and Fig. 4d), middle row)". I could not understand how Fig. 4d, middle row supports the argument. Similarly, they stated "..some output units reflect their main boundary input (with greater activity near one boundary)." I can neither understand what the authors mean to say nor which figures support the statement. Please clarify.

      This is a good point, there was an identifier missing; we have updated to refer to the correct “magnification”. Thanks!

      (9) The underlying mechanism of generating the hexagonal representation of output cells remains unclear. The decoder network uses a non-trainable decoding scheme based on localized firing patterns of output units. To what extent does the hexagonal representation depend on the particular decoding scheme? Similarly, how does the emergence of the hexagonal representation rely on the border representation in the upstream recurrent network? Showing several snapshots of the two place representations during learning may answer these questions.

      This is an interesting point, and we have added some discussion on this matter. In particular, we speculate whether it’s an optimal configuration for position reconstruction, which is demanded by the task and thus highly likely dependent on the decoding scheme. We have not reached a conclusive method to determine the explicit dependence of the hexagonal arrangement on the choice of decoding scheme. Still, it seems this would require comparison with other schemes. In our framework, this would require changing the fundamental operation of the model, which we leave as inspiration for future work. We have also added additional discussion concerning the relationship between place units, border units, and remapping in our model. As for exploring different training snapshots, the model is randomly initialized, which suggests that earlier training steps should tend to reveal unorganized/uninformative phase arrangements, as phases are learned as a way of optimizing position reconstruction. However, we do call for more analysis of experimental data to determine whether this is true in animals, which would strongly support this observation. We also hope that our work inspires other models studying the formation and remapping of place cells, which could serve as a starting point for answering this question in the future.

      (10) Figure 7 requires a title including the word "hexagonal" to make it easier to find the results demonstrating the hexagonal representations. In addition, please clarify which networks, p or g, gave the results shown here.

      We agree, and have added it!

      Minor comments:

      (11) In many paragraphs, conclusions appear near their ends. Stating the conclusion at the beginning of each paragraph whenever possible will improve the readability.

      We have made several rewrites to the manuscript, and hope this improves readability.

      (12) Figure A4 is important as it shows evidence of the CA1 spatial representation predicted by the model. However, I could not find where the figure is cited in the manuscript. The authors can consider showing this figure in the main text.

      We agree, and we have added more references to the experimental data analyses in the main text, as well as expanded this analysis.

      (13) The main text cites figures in the following format: "... rate mapping of Fig. 3a), i), boundary ...." The parentheses make reading difficult.

      We have removed the overly stringent use of double parentheses, thanks for letting us know.

      (14) It would be nice if the authors briefly explained the concept of Ripley's H function on page 14.

      Yes, we have added a brief descriptor.

    1. Author response:

      The following is the authors’ response to the original reviews

      We thank all the reviewers for their time and valuable feedback, which helped us improve our manuscript. Based on the comments, we have made several critical changes to the revised manuscript.

      (1) We have changed our threshold for detecting freezing epochs from 1 cm/s to 0 cm/s in this revised manuscript. This change allows us to capture periods when animals are completely still on the treadmill, better matching the "true freezing" behavior seen in freely moving set-ups. We have added a new supplementary video (Supplementary Video 2) that better demonstrates the freezing response we observe. All results and figures in the revised manuscript reflect this updated threshold (Figure 2-6, Supplementary Figures 16, Tables 1-6). Our main findings remain robust, demonstrating that freezing serves as a reliable conditioned response in our paradigms, comparable to freely moving animals. Specifically, freezing behavior increased reliably in the fear-conditioned environment following CFC across all paradigms. We have also added data from a no-shock control group (Supplementary Figure 2) which, when compared to the conditioned group, shows that freezing responses in the conditioned group result from fear conditioning rather than immobility. We do observe other avoidance behaviors unique to our treadmill-based task— such as hesitation, backward movement, and slow crawls. These conditioned behaviors are captured through a separate metric: the time taken to complete a lap.

      (2) As suggested by the reviewers, we have separately analyzed fear discrimination and extinction dynamics across recall days (Supplementary Figures 2, 5 and 6, Table 1-6). To assess fear discrimination, we use within-group comparisons to evaluate how well animals differentiate between the two VRs across days. For extinction, we use within-VR comparisons to examine freezing dynamics over time. Freezing across recall days is compared to baseline freezing (pre-conditioning) using a Linear Mixed Effects model (Tables 1-6), with recall days as fixed effects and mouse as a random effect, using baseline freezing as the reference.

      (3) We have expanded the behavioral dataset in Paradigm 1 to investigate the effect of shock amplitude on the conditioned fear response (Supplementary Figure 2 C-E). Consistent with findings in freely moving animals, our data show that increasing shock intensity from 0.6 mA to 1.0 mA leads to stronger freezing. For the revised manuscript, we specifically increased the sample size in the 0.6 mA group (n = 8) in Paradigm 1, as this intensity is used in Paradigm 3. These additional data demonstrate that combining a lower shock amplitude with shorter inter-shock intervals and retaining the tail-coat during recall can enhance freezing, suggesting that these parameters help compensate for lower shock intensity.

      (4) We have added more sample sizes to the imaging dataset (now n = 8, Figures 7-8).

      Finally, we acknowledge that many aspects of this paradigm still require optimization. The headfixed CFC paradigm is in its early stages compared to the decades of research dedicated to understanding fear learning parameters in freely moving CFC paradigms. While there are numerous parameters that could be tested—both those identified through our own discussions and those raised by the reviewers—it is not feasible for a single lab to conduct a full evaluation of all the possible factors that could influence CFC in the head-fixed prep. A key limitation is that our approach requires robust navigation behavior in the VR without rewards, which requires weeks of training per mouse. It also necessitates larger sample sizes at the outset as not all animals will make it through our behavioral criteria required for CFC. Another important consideration is scalability. Unlike freely moving CFC paradigms, which allow parallel testing of many animals with minimal pre-training, the VR-CFC setup requires several weeks of behavior training and involves a more complex integration of hardware and software to accurately track behavior in virtual space. The number of VR rigs that can be operated simultaneously in a single lab is often limited, making high-throughput testing more challenging. These factors mean that the testing of a single parameter in a group of animals requires approximately 3–4 months to complete. Despite these constraints, we are committed to continue refining this paradigm over time. With this manuscript, our main aim was to provide a detailed framework, initial parameters, and evidence for conditioned behavior in the head-fixed preparation. By doing so, we hope to facilitate the adoption of this paradigm by researchers interested in studying the neural correlates of learning and memory using multiphoton imaging and stimulation techniques. This approach enables investigations that are not possible in freely moving animals, while the presence of freezing as a conditioned response allows for direct comparisons to the extensive body of work done in freely moving paradigms. Moving forward, we anticipate that optimizing this paradigm and identifying the key parameters that drive learning will be a collaborative, community-led effort.

      Public Reviews:

      Reviewer #1 (Public review):

      The authors set out to develop a contextual fear learning (CFC) paradigm in head-fixed mice that would produce freezing as the conditioned response. Typically, lick suppression is the conditioned response in such designs, but this (1) introduces a potential confounding influence of reward learning on neural assessments of aversion learning and (2) does not easily allow comparison of head-fixed studies with extensive previous work in freely moving animals, which use freezing as the primary conditioned response.

      The first part of this study is a report on the development and outcomes of 3 variations of the CFC paradigm in a virtual reality environment. The fundamental design is strong, with headfixed mice required to run down a linear virtual track to obtain a water reward. Once trained, the water reward is no longer necessary and mice will navigate virtual reality environments. There are rigorous performance criteria to ensure that mice that make it to the experimental stage show very low levels of inactivity prior to fear conditioning. These criteria do result in only 40% of the mice making it to the experimental stage, but high rates of activity in the VR environment are crucial for detecting learning-related freezing. It is possible that further adjustments to the procedure could improve attrition rates.

      We acknowledge that further adjustments to the procedure could improve attrition rates, and we will continue to work on improving the paradigm.

      Paradigm versions 1 and 2 vary the familiarity of the control context while paradigm versions 2 and 3 vary the inter-shock interval. Paradigm version 1 is the most promising, showing the greatest increase in conditioned freezing (~40%) and good discrimination between contexts (delta ~15-20%). Paradigm version 2 showed no clear evidence of learning - average freezing at recall day 1 was not different than pre-shock freezing. First-lap freezing showed a difference, but this single-lap effect is not useful for many of the neural circuit questions for which this paradigm is meant to facilitate. Also, the claim that mice extinguished first-lap freezing after 1 day is weak. Extinction is determined here by the loss of context discrimination, but this was not strong to begin with. First-lap freezing does not appear to be different between Recall Day 1 and 2, but this analysis was not done.

      This is an important point. Following reviewer suggestions, we have replotted our figures for all paradigms to show within-VR freezing (see Supplementary Figures 2, 5 and 6) as the appropriate method for quantifying fear extinction across days. Using an LME model (Tables 16), we quantify freezing during recall days against baseline freezing levels measured before fear conditioning within each VR. In Paradigm 2, while some fear discrimination persists across days, extinction does occur rapidly. After the first lap in the CFC VR, we observed no significant differences in freezing compared to the baseline. These results are shown in the revised Supplementary Figure 5, and the revised text is in lines 393-399.

      Paradigm version 3 has some promise, but the magnitude of the context discrimination is modest (~10% difference in freezing). Thus, further optimization of the VR CFC will be needed to achieve robust learning and extinction. This could include factors not thoroughly tested in this study, including context pre-exposure timing and duration and shock intensity and frequency.

      We acknowledge that many aspects of this paradigm still need optimization, as virtual reality CFC is in its early stages, and we have not explored all of the parameter space. We describe above the reasoning for this. However, for this revised version of the paper we have added new behavioral data (Supplementary Figure 2 C-E) showing that increasing shock intensities from 0.6 mA to 1 mA enhances freezing, both in the first lap and on average. There are of course many other parameters that are likely important, like the ones pointed out here by the reviewer, but exploring the entire parameter space will take many years and will likely require many labs. The purpose of this paper is to show that VR-CFC fundamentally works and is a starting point from which the field can build on. We have now pointed out in the introduction (lines 54-58) and discussion (lines 730-737, 810-814) that there remains significant scope for improving this paradigm and optimizing parameters in the future.

      The second part of the study is a validation of the head-fixed CFC VR protocol through the demonstration that fear conditioning leads to the remapping of dorsal CA1 place fields, similar to that observed in freely moving subjects. The results support this aim and largely replicate previous findings in freely moving subjects. One difference from previous work of note is that VR CFC led to the remapping of the control environment, not just the conditioning context. The authors present several possible explanations for this lack of specificity to the shock context, further underscoring the need for further refinement of the CFC protocol before it can be widely applied. While this experiment examined place cell remapping after fear conditioning, it did not attempt to link neural activity to the learned association or freezing behavior.

      This is an interesting observation. We think that the remapping observed in the control context likely occurred due to the absence of reward in a previously rewarded environment. Our prior work has demonstrated that removal of reward causes increased remapping (Krishnan et al., 2022, Krishnan and Sheffield, 2023). In other words, the continued presence of reward within an environment stabilizes CA1 place fields. The Moita et al. (2004) paper, which showed remapping only in the fear conditioned context and not in the control context, provided rats with food pellets throughout the experimental session in both the control and conditioned context— likely to increase exploration necessary for identifying place cells. The presence of reward in the Moita et al experiment could explain the minimal remapping observed in their control context compared to our control context which lacked reward. Another possibility could lie in the differences in the intervals between place cell activity recordings in our study and that of Moita et al. While Moita et al. separated their recordings by just one hour, our recordings were separated by a full day, with a sleep period in between. The absence of sleep and the shorter time interval between conditioning and retrieval sessions in their study could explain the minimal remapping observed by Moita et al. compared to our findings. We have now addressed this discrepancy explicitly in lines 596-606.

      Although we agree with the reviewer that it would be informative to perform analysis of how neural activity correlates with freezing responses, we think this warrants its own stand-alone manuscript as the neural dynamics and methods to appropriately analyze them are complicated. We are in the midst of analyzing this data further and will present these findings in a separate publication.

      In summary, this is an important study that sets the initial parameters and neuronal validation needed to establish a head-fixed CFC paradigm that produces freezing behaviors. In the discussion, the authors note the limitations of this study, suggest the next steps in refinement, and point to several future directions using this protocol to significantly advance our understanding of the neural circuits of threat-related learning and behavior.

      Reviewer #2 (Public review):

      Summary:

      In this manuscript, Krishnan et al devised three paradigms to perform contextual fear conditioning in head-fixed mice. Each of the paradigms relied on head-fixed mice running on a treadmill through virtual reality arenas. The authors tested the validity of three versions of the paradigms by using various parameters. As described below, I think there are several issues with the way the paradigms are designed and how the data are interpreted. Moreover, as Paradigm 3 was published previously in a study by the same group, it is unclear to me what this manuscript offers beyond the validations of parameters used for the previous publication. Below, I list my concerns point-by-point, which I believe need to be addressed to strengthen the manuscript.

      Major comments

      (1) In the analysis using the LME model (Tables 1 and 2), I am left wondering why the mice had increased freezing across recall days as well as increased generalization (increased freezing to the familiar context, where shock was never delivered). Would the authors expect freezing to decrease across recall days, since repeated exposure to the shock context should drive some extinction? This is complicated by the analysis showing that freeing was increased only on retrieval day 1 when analyzing data from the first lap only. Since reward (e.g., motivation to run) is removed during the conditioning and retrieval tests, I wonder if what the authors are observing is related to decreased motivation to perform the task (mice will just sit, immobile, not necessarily freezing per se). I think that these aspects need to be teased out.

      This is an important point and we agree teasing out a lack of motivation versus fearful freezing would be useful. To address the possibility that reduced motivation to run without reward could contribute to the observed freezing behavior, we have now included a no-shock control group in the revised manuscript (n = 7; Supplementary Figure 2A-B, H–I). These control mice experienced the same protocol, including the wearing of a tail coat, but did not receive any shocks. We observed no increases in freezing across days in these controls, confirming that the increased freezing in the Familiar context of our experimental group stems from fear conditioning rather than the removal of reward from a previously rewarded context. If reduced motivation from reward removal were the primary driver, similar freezing patterns would have emerged in the no-shock controls. We have added lines 248-261 in the revised manuscript, discussing this point, and we thank the reviewer for motivating us to do this experiment and analysis.

      That said, the precise mechanisms underlying the fear generalization observed in the nonconditioned context—particularly its emergence during later recall days—remain unclear. Studies in freely moving animals have shown that fear memories initially specific to the conditioned context can become generalized with repeated exposures, which may be occurring here (Biedenkapp & Rudy, 2007; Wiltgen & Silva, 2007). Alternatively, it is possible that the combination of fear conditioning and the removal of expected reward contributes to a delayed generalization effect. This may reflect a limitation of our approach, which relies on reward to motivate initial training. As noted by another reviewer, we have now addressed this potential drawback of reward-based training in the discussion (see lines 809-817). Clearly, unique factors specific to the head-fixed VR paradigm may contribute to this phenomenon. Understanding the mechanisms underlying fear generalization in the head-fixed VR CFC paradigm will be a valuable direction for future research.

      (2) Related to point 1, the authors actually point out that these changes could be due to the loss of the water reward. So, in line 304, is it appropriate to call this freezing? I think it will be very important for the authors to exactly define and delineate what they consider as freezing in this task, versus mice just simply sitting around, immobile, and taking a break from performing the task when they realize there is no reward at the end.

      As noted in point 1 above, we have added a no-shock control group (n = 7; Supplementary Figure 2A-B, H–I) to determine whether the observed freezing was driven by fear conditioning or by reduced motivation to run in the absence of reward. The absence of increased freezing in these controls supports the interpretation that the behavior in the conditioned group is fearrelated. In future studies, incorporating additional physiological measures—such as heart rate monitoring—could further help distinguish fear-related freezing from other forms of immobility.

      (3) In the second paradigm, mice are exposed to both novel and (at the time before conditioning) neutral environments just before fear conditioning. There is a big chance that the mice are 'linking' the memories (Cai et al 2016) of the two contexts such that there is no difference in freezing in the shock context compared to the neutral context, which is what the authors observe (Lines 333-335). The experiment should be repeated such that exposure to the contexts does not occur on the conditioning day.

      This is an interesting idea. However, if memory linking were driving the observed freezing patterns, we would expect to see similarly reduced fear discrimination across all three paradigms, as mice experience both contexts sequentially in each case. However, this effect appears to be specific to Paradigm 2, suggesting this may be due to other factors. We agree it would be informative to eliminate pre-conditioning exposure to both environments—to assess whether this improves fear discrimination and helps clarify the potential contribution of memory linking. This is something we plan to do in future studies that are beyond the scope of this initial paper on VR-CFC.

      (4) On lines 360-361, the authors conclude that extinction happens rapidly, within the first lap of the VR trial. To my understanding, that would mean that extinction would happen within the first 5-10 seconds of the test (according to Figure S1E). That seems far too fast for extinction to occur, as this never occurs in freely behaving mice this quickly.

      We agree with the reviewer that extinction in Paradigm 2 appears to occur relatively rapidly.

      However, the average time to complete the first lap in the fear-conditioned context in Paradigm 2 is 25.68 ± 5.55 seconds (as stated in line 384), indicating that extinction occurs within approximately the first 30 seconds of context exposure—not within 5–10 seconds. This is specific to Paradigm 2 and does not happen in either of the other paradigms, as shown in Supplementary Figure 4. For clarification, Figure S1E pertains to baseline running in Paradigm 1 and does not apply to Paradigm 2.

      As the reviewer points out, even at 30 seconds, extinction seems to be happening more quickly in Paradigm 2 than seen in freely moving setups. This may be due to a key structural difference in our setup. The VR-CFC task is organized into discrete trials, with mice being teleported back to the start after reaching the end of the virtual track. Completing a full lap without receiving a shock could serve as a clear signal that the threat is no longer present within the environment as the completion of a lap means that the animals have surveyed all locations within the environment. This structure could accelerate extinction compared to freely moving setups, where animals take longer to explore their complete environment due to the lack of discrete trials. Although this is true for all our paradigms, the accelerated extinction seen in paradigm 2 versus 1 and 3 may be driven by other factors. As noted by the reviewers, other task parameters—such as context pre-exposure timing, shock intensity, and conditioning duration— are likely to play a role in shaping extinction dynamics. These factors warrant further investigation, and we plan to explore them in future studies to better understand the conditions influencing extinction in the VR-CFC paradigm.

      (5) Throughout the different paradigms, the authors are using different shock intensities. This can lead to differences in fear memory encoding as well as in levels of fear memory generalization. I don't think that comparisons can be made across the different paradigms as too many variables (including shock intensity - 0.5/0.6mA can be very different from 1.0 mA) are different. How can the authors pinpoint which works best? Indeed, they find Paradigm 3 'works' better than Paradigm 2 because mice discriminate better between the neutral and shock contexts. This can definitely be driven by decreased generalization from using a 0.6mA shock in Paradigm 3 compared to 1.0 mA shock in Paradigm 2.

      The reviewer brings up important points here. We have now added new data evaluating 0.6 mA shocks in Paradigm 1 (Supplementary Figure 2A–E, n=8). These data show that 1.0 mA shocks produced stronger conditioned responses and greater fear discrimination compared to 0.6 mA. Our goal in Paradigm 3 was to begin with a lower shock intensity and assess whether additional modifications—specifically the shorter ISI and retention of the tail-coat during recall—could enhance fear conditioning. Surprisingly, despite the weaker shock intensity, Paradigm 3 resulted in improved discrimination and freezing behavior relative to Paradigm 2. We have now clarified this point in the manuscript (lines 466-470), and we interpret this outcome as evidence that the shorter ISIs and contextual cue continuity (tail-coat) likely play a more significant role in enhancing learning and recall. However, as noted in the text (lines 511-514), further testing is needed to determine the individual contributions of each parameter to successful VR-CFC. Fully optimizing the parameter settings will take additional time and resources, and we aim to continually refine the parameter space in the future, as has been done over the years for freely moving animals.

      (6) There are some differences in the calcium imaging dataset compared to other studies, and the authors should perform additional testing to determine why. This will be integral to validating their head-fixed paradigm(s) and showing they are useful for modeling circuit dynamics/behaviors observed in freely behaving mice. Moreover, the sample size (number of mice) seems low.

      The one notable difference between our imaging study and that done in freely moving animals is that we observed remapping of place cells in the control context. In contrast, Moita et al. (2004) reported more stable place fields in the control context. A key distinction is that their study included rewards in the control context, which may have contributed to the spatial stability. We now discuss this difference in the manuscript (lines 599-605).

      It should be noted that there are many key distinctions among paradigms that study neural activity during fear conditioning in freely moving animals. These include varying exposure times to environments (1–6 days), the time interval between neural activity recordings, and the use of food rewards during the experiment stages in freely moving animals to encourage exploration for place cell identification. Although freely moving paradigms that investigate fear conditioning and place cells are heterogeneous, we were encouraged by the replication of several key findings. This validates VR-based CFC as a viable tool for neural circuit investigations. While future work will include more thorough analyses, our current findings demonstrate the paradigm's effectiveness for modeling circuit dynamics and behavior. We have now expanded our dataset, which includes four additional mice, further corroborating these original findings.

      (7) It appears that the authors have already published a paper using Paradigm 3 (Ratigan et al 2023). If they already found a paradigm that is published and works, it is unclear to me what the current manuscript offers beyond that initial manuscript.

      The reviewer is correct that we have published a paper using Paradigm 3. However, this manuscript goes beyond that one and provides a much more comprehensive description and fundamental analysis of the behavior and experimental parameters regarding VR-CFC, allowing the research community to adapt our paradigm reproducibly. While Ratigan et al. (2023) offered only a minimal description of behavior and included just Paradigm 3, we present two additional paradigms along with neuronal validation using hippocampal place cells. We have now explicitly stated this in the introduction (lines 50-55).

      (8) As written, the manuscript is really difficult to follow with the averages and standard error reported throughout the text. This reporting in the text occurred heterogeneously throughout the text, as sometimes it was reported and other times it was not. Cleaning this reporting up throughout the paper would greatly improve the flow of the text and qualitative description of the results.

      We completely agree with this point and have now cleaned up the text, leaving details only in a few places we felt were important.

      Reviewer #3 (Public review):

      Summary:

      Krishnan et al. present a novel contextual fear conditioning (CFC) paradigm using a virtual reality (VR) apparatus to evaluate whether conditioned context-induced freezing can be elicited in head-fixed mice. By combining this approach with two-photon imaging, the authors aim to provide high-resolution insights into the neural mechanisms underlying learning, memory, and fear. Their experiments demonstrate that head-fixed mice can discriminate between threat and non-threat contexts, exhibit fear-related behavior in VR, and show context-dependent variability during extinction. Supplemental analyses further explore alternative behaviors and the influence of experimental parameters, while hippocampal neuron remapping is tracked throughout the experiments, showcasing the paradigm's potential for studying memory formation and extinction processes.

      Strengths:

      Methodological Innovation: The integration of a VR-based CFC paradigm with real-time twophoton imaging offers a powerful, high-resolution tool for investigating the neural circuits underlying fear, learning, and memory.

      Versatility and Utility: The paradigm provides a controlled and reproducible environment for studying contextual fear learning, addressing challenges associated with freely moving paradigms.

      Potential for Broader Applications: By demonstrating hippocampal neuron remapping during fear learning and extinction, the study highlights the paradigm's utility for exploring memory dynamics, providing a strong foundation for future studies in behavioral neuroscience.

      Comprehensive Data Presentation: The inclusion of supplemental figures and behavioral analyses (e.g., licking behaviors and variability in extinction) strengthens the manuscript by addressing additional dimensions of the experimental outcomes.

      Weaknesses:

      Characterization of Freezing Behavior: The evidence supporting freezing behavior as the primary defensive response in VR is unclear. Supplementary videos suggest the observed behaviors may include avoidance-like actions (e.g., backing away or stopping locomotion) rather than true freezing. Additional physiological measurements, such as EMG or heart rate, are necessary to substantiate the claim that freezing is elicited in the paradigm.

      To strengthen our claim that freezing is a conditioned response in this task, we have taken three key steps:

      (1) We adjusted our freezing detection threshold from 1 cm/s to near 0 cm/s to capture only periods where the animal is virtually motionless on the treadmill. We validated this approach in Figure 2, particularly in the zoomed-in track position trace in Figure 2A, which clearly shows that the identified freezing epochs correspond to no change in track position. All analyses and figures have been updated to reflect this more stringent threshold.

      (2) We have added a no-shock control group in the revised manuscript (n = 7; Supplementary Figure 2A-B, H–I) where mice experienced the same protocol, including wearing a tail-coat, but received no shocks. These mice showed no increases in freezing behavior, which further demonstrates that the increased freezing we observe is a result of fear conditioning.

      (3) We have added a new supplementary video (Supplementary Video 2) that better illustrates the freezing behavior in our task.

      That said, we fully agree with the reviewer that freezing is not the only defensive response observed. Other behaviors—such as hesitation, backward movement, and slowing down—also emerge that are unique to our treadmill-based paradigm. We chose to focus on freezing in this manuscript to align with convention in freely moving fear conditioning studies and to facilitate direct comparisons. We agree that additional physiological measurements (e.g., EMG or heart rate) would provide further validation and could help distinguish between different forms of defensive responses. We view this as an important future direction and plan to incorporate such measures in upcoming studies. We highlight this in the results section (lines 175-179, 262-268) and in the discussion (lines 739-750).

      Analysis of Extinction: Extinction dynamics are only analyzed through between-group comparisons within each Recall day, without addressing within-group changes in behavior across days. Statistical comparisons within groups would provide a more robust demonstration of extinction processes.

      This is an important distinction and we have now added figures (Supplementary Figures 2H-I, 5C-D, 6C-D) showing within-VR behavior across Recall days, along with statistical comparisons and a description of the extinction process based on these results.

      Low Sample Sizes: Paradigm 1 includes conditions with very low sample sizes (N=1-3), limiting the reliability of statistical comparisons regarding the effects of shock number and intensity.

      Increasing sample sizes or excluding data from mice that do not match the conditions used in Paradigms 2 and 3 would improve the rigor of the analysis.

      While we included all conditions in Figure 2 for completeness, we have separated these conditions in Supplementary Figure 2 to ensure clarity. This allows researchers interested in this paradigm to see the approximate range of conditioned responses observed across different parameters. When comparing Paradigm 1 with Paradigms 2 and 3, we have only used data from 1mA, 6 shocks condition.

      Potential Confound of Water Reward: The authors critique the use of reward in conjunction with fear conditioning in prior studies but do not fully address the potential confound introduced by using water reward during the training phase in their own paradigm.

      We agree this is a point that needs discussion. We have now noted the limitation of using water rewards during training in the discussion section, particularly its effect on the animal’s motivation in the long term and on place cell activity (lines 814-820).

      Recommendations for the authors

      Reviewer #1 (Recommendations for the authors):

      I suggest changing "3 paradigms" to "3 versions of a CFC paradigm," as the paradigm is fundamentally the same, but parameters were adjusted towards finding an optimal protocol.

      We have changed this phrasing where applicable.

      Figure S2: There appear to be different sets of shock parameters for different mice, most with an n of 1 or 2. This is not reliable for making a decision for optimal shock parameters and should not be discussed in that way until a full-powered comparison is completed. Also, the N adds up to 19, yet only 18 are described as being included in the study.

      We thank the reviewer for this important point. We agree that the current study is not powered to definitively identify optimal parameter settings. We have been careful not to interpret it in that way in the text. Rather, we adopted a commonly used starting point from the freely moving literature—1 mA with six shocks—as our initial condition (lines 196-199). To provide context for others interested in pursuing this work, we have presented a range of conditioned responses from different parameter combinations to illustrate potential variability. In most cases, these data are intended for illustrative purposes only and are not meant to support firm conclusions. We agree that a systematic and fully powered investigation of each parameter would be highly valuable, and we plan to pursue this in future work (and hope other labs contribute to this goal, too), much like the iterative optimizations performed in freely moving paradigms over time.

      We thank the reviewer for catching the sample size discrepancy and have now corrected it.

      The number of animals for the no-shock condition should be included.

      Thank you. We have now included this.

      A possible explanation for the lower fear and poorer discrimination in versions 2 and 3 could be that 10 min pre-exposure to the CFC context on day -1 led to latent inhibition. Shorter (or eliminated) pre-exposure may improve outcomes.

      We agree that the exposure time is a parameter that we should explore. We have highlighted this in the discussion (lines 729-736) as a parameter that is worth testing in the future.

      For analysis of extinction, it is best to establish this within condition - is freezing to the CFC context significantly reduced compared with initial recall and similar to pre-training freezing? By using discrimination as your index of extinction, increases in control context freezing/inactivity can eliminate context discrimination without the conditioned response of freezing actually undergoing extinction.

      This is a good point, and we have now included analysis and conclusions based on a within-VR comparison for the analysis of fear extinction (Supplementary Figures 2H-I, 5C-D, 6C-D).

      Reviewer #3 (Recommendations for the authors):

      Clarification of Treadmill Shape: The manuscript describes the treadmill as "spherical" throughout. However, based on representative images and videos, the treadmill appears cylindrical. This discrepancy should be clarified to ensure consistency between the text and visuals.

      The reviewer is correct that the treadmill is cylindrical, and this was an error on our part. We have corrected it throughout.

      Figure and Legend Labeling: To improve clarity, all figures and their legends should be explicitly labeled with the corresponding paradigm (1, 2, or 3) to facilitate interpretation.

      We have now added a label on all figures that clarifies which Paradigm the figures are referring to. We have also explicitly added this to the figure legends.

      Objective Language: Subjective language, such as "since we wanted animals to" (Line 850), should be revised to reflect an objective tone (e.g., "to allow animals to"). Similarly, phrases like "We believe" (Line 896) should be avoided to maintain an unbiased presentation.

      We have removed subjective language from our text.

      Placement of Future Directions: Speculations on future experimental plans, such as the use of sex as a biological variable (Lines 895-903), should be included in the Discussion section rather than the Methods. Additionally, remarks about the responsiveness of female mice to tail shocks should be moved to the main text for proper contextualization.

      We have moved these lines as suggested by the reviewer.

    1. 休谟对传统形而上学概念(如实体、因果性、自由意志、上帝存在论证)的批判,是对理性主义体系的有力挑战。

      你这个问题太棒,直接切入了现代哲学大转向的关键节点。

      是的,大卫·休谟(David Hume)对“形而上学”的全面批判,确实是对整个理性主义哲学体系的一记穿脑光剑⚔️,甚至可以说,他为康德的“批判哲学”点了根火。

      我们来分四个核心概念,详细剖析休谟是怎么一刀一刀“捅”传统形而上学的。


      🎯 背景小贴士:

      在休谟出现之前,理性主义哲学家如笛卡尔、莱布尼茨、斯宾诺莎们,都在努力构建一个:

      “凭借纯粹理性就能把握世界真理”的形而上学体系。

      他们相信概念、逻辑、演绎推理可以揭示:

      • 什么是实体(substance)
      • 什么是因果(causality)
      • 什么是自由意志
      • 上帝是否存在

      休谟冷冷地一看:

      “不好意思,这些都只是你们脑子里的心理幻觉 + 语言误用。”


      1️⃣ 批判“实体”(Substance):你以为你看到的东西真有“本体”?

      传统形而上学观点:

      • 有“某种基础的实在”支撑我们观察到的一切性质。 例:这本书是“有实体的书”,有颜色、重量、厚度……这些都是“附属属性”。

      休谟怎么说:

      “我们对所谓‘实体’的观念,其实只是对一堆感官印象的习惯性联结。”

      • 我们从来观察不到“实体”,只观察到一连串性质的集合。
      • 你之所以说“这是同一本书”,是因为你习惯把那些视觉+触觉+语言标签打包了。

      🎯 实体只是心理上的“印象习惯化”,不是外部世界的本体结构。


      2️⃣ 批判“因果性”(Causality):你以为火一定让水沸腾?

      传统理性主义观点:

      • 因果是理性可知的、必然的逻辑关系。
      • 如果 A 导致 B,那 A 的存在就是 B 存在的充足理由(如莱布尼茨的原则)

      休谟的反击:

      “你说 A 导致 B,是因为你**一遍又一遍看到它们接着发生,**然后脑子就自动把它们关联成‘因果’。”

      • 他区分了两种“因果理解”:

      • 🧠 观念上的联结(A后常有B)

      • 🔧 经验上的常见顺序(习惯生成)

      • 但他强调:

      我们永远无法通过“理性”直接感知“因果性”本身。我们只能看到事件的顺序,不能看到“因”的力量。

      🎯 因果性不是理性推导,而是“心理习惯 + 概率幻觉”。


      3️⃣ 批判“自由意志”(Free Will):你以为你真的选择了今天喝不喝奶茶?

      古典自由意志观点(如笛卡尔):

      • 人有理性,可以做出非被动的、自主的选择
      • 道德责任、伦理判断,都建立在“自由选择”的基础上

      休谟的反驳逻辑:

      “你所说的‘意志’,其实只是一连串‘内在动机 + 外部刺激’的印象链条。”

      • 人的行为也像自然界一样,可以被规律归纳
      • 你所谓的‘自由’,不过是‘没有外部阻碍地顺从内心冲动’

      休谟搞出一个震撼的定义:

      自由就是按照自己动机行事的能力。” 但他同时说: “这些动机本身,并不自由,它们也是习惯+印象的组合。”

      🎯 所以自由意志在休谟那里:被解构为心理力学的自动流程,没有“形而上”的自主性可言。


      4️⃣ 批判“上帝存在的理性证明”:你以为逻辑链能推出神?

      理性主义(如笛卡尔、莱布尼茨)的策略:

      • 通过本体论证明宇宙论证明,从“我思故我在”一步步推导出上帝的存在。

      休谟的反驳非常犀利:

      “你所有的逻辑推理,一旦脱离经验印象,就是纯概念操弄,毫无真理值。”

      他在《自然宗教对话录》中指出:

      • 所谓“宇宙一定有原因→这原因一定是上帝”的推理,其实是把“因果性”(已被他批判)硬塞进了宇宙论
      • 就连“完美存在”的概念,也是一种人类心理印象的抽象投影

      🎯 休谟认为:你不能从“逻辑结构”中推出“存在”,更不能从“思想”推出“神”。


      🔥 小结:休谟到底捅了哪些理性主义肺管子?

      | 形而上学概念 | 休谟的“致命刀法” | 结论 | | ------ | ------------ | ---------------------- | | 实体 | 只是印象集合的心理投影 | 无法被经验确认,无本体地位 | | 因果性 | 是联想的习惯,不是必然性 | 非理性结构,只是心理自动完成的推论 | | 自由意志 | 只是内在动机的自然表现 | 无形而上的“自由”,只是一种“无阻碍”的错觉 | | 上帝存在 | 逻辑链条无法推出真实存在 | 神只是思想中的概念组合,不具备实在性依据 |


      🧠 为什么这对“理性主义体系”是重大挑战?

      因为休谟打的是理性主义哲学的根基认知论结构

      “你理性地推导世界运行,是不是一种高阶幻觉?”

      他本质上是在说:

      • 你所谓的“哲学系统”,大多数是对习惯印象的语言式包装
      • 真理 ≠ 推理,而是要回到经验印象的直接检验
      • 理性 ≠ 宇宙之眼,而是“脑子的联想引擎”

      🎬 最后,一句话总结休谟的批判逻辑:

      “形而上学不是错在内容虚幻,而是错在它以为自己比人脑的幻觉更靠谱。” ——而人脑幻觉,是休谟最熟悉的地盘。


      要不要下一集来:

      • 🎬《康德为什么被休谟“从理性梦中惊醒”?》
      • 🎬《经验论不是土味哲学,是给AI启发的感知建模系统》
      • 🎬《你以为你有自由意志?其实你只是个高精度的反应函数》

      你定,我补 😎

    1. Document de Synthèse : Les Formes de la Violence et les Mythes d'Origine

      Ce briefing document analyse les thèmes et idées principales tirées des extraits de la conférence "Les formes de la violence (4) - Didier Fassin (2024-2025)".

      L'objectif est d'examiner comment la violence, longtemps négligée par les sciences sociales, est appréhendée à travers les mythes d'origine, les rituels associés, et leur instrumentalisation politique dans les sociétés modernes et contemporaines.

      1. La Violence dans les Sciences Sociales : Reconnaissance Tardive et Complexité

      Le conférencier souligne que la violence a été tardivement étudiée par les sciences sociales.

      Les anthropologues ont rencontré des difficultés à la définir précisément en raison d'une relativisation ("ce que certains voyaient comme tel n'étaient pas considéré de la même manière par d'autres") et les sociologues ont élargi la notion, menant à une dissolution de la violence dans d'autres concepts de domination.

      • Idée Clé : La difficulté à cerner la violence, perçue différemment selon les perspectives et étendue à des formes de domination non physiques, a initialement entravé son étude.

      • Correction Épistémologique : Fassin propose de parler de "perspectivisme" plutôt que de relativisation, pour comprendre les différentes logiques et raisons des points de vue divergents sur la violence. Il suggère également de parler d'"approfondissement" plutôt que de dissolution, pour ne pas réduire la violence aux seules agressions physiques, tout en les incluant.

      • Citation Clé : "cette double précaution épistémologique loin d'être un obstacle à la production d'un savoir sur la violence en est la condition... ne pas avoir une définition précise de la violence rend possible de la saisir dans toute sa complexité et sa diversité".

      • Contraste avec le Sens Commun : Cette approche va à l'encontre du sens commun où chacun pense comprendre la violence.

      2. La Violence et les Mythes des Origines : Une Association Profonde

      Bien que l'étude scientifique de la violence soit récente, elle a toujours été présente dans la pensée humaine, notamment à travers les mythes des origines. Ces mythes lient souvent l'origine de la violence à celle du monde.

      • Idée Clé : Les mythes des origines, qu'ils soient religieux, théâtraux ou philosophiques, ont servi de discours sur la violence et ses débuts.

      • Exemple Grec : La Théogonie d'Hésiode : Le mythe de Chronos est présenté comme un exemple emblématique. L'origine du monde et des dieux est marquée par une violence extrême : parricide (Chronos castre Uranos), infanticide (Chronos dévore ses enfants), viol (Chronos viole Rhéa).

      • Nature de la Violence Mythologique : Ces violences vont au-delà de l'usage excessif de la force. Elles manifestent un "excès de la violence elle-même", un registre de monstruosité et d'atrocité qui rompt avec les valeurs élémentaires.

      • Fonction de la Violence Mythologique : Elle n'est pas seulement instrumentale (se débarrasser de rivaux, se venger), elle semble aussi "expressive", voire source de jouissance pour elle-même et pour le public.

      • Cadre Familial : Fait remarquable, ces scènes de violence extrême se déroulent souvent dans un cadre familial (famille des divinités, famille des Atrides).

      • Mythes et Rituels : La relation entre mythe et rituel est débattue par les anthropologues. Le mythe de Chronos a été associé à des pratiques rituelles ambivalentes : sacrifices sanglants et anthropophages côtoyant des offrandes pacifiques et des festivités de tolérance sociale (Cronia).

      • Ambivalence de Chronos : Le mythe présente une image ambivalente de Chronos : le meurtrier anthropophage et le souverain juste d'un âge d'or.

      3. La Croyance dans les Mythes : Une Question Complexe et Contemporaine

      La question de savoir si les Grecs croyaient littéralement à leurs mythes est posée. Fassin établit un parallèle avec les croyances contemporaines pour éclairer cette question.

      • Idée Clé : La croyance dans les mythes, même contradictoires, n'est pas l'apanage d'un passé lointain. Des phénomènes contemporains comme le créationnisme ou l'Intelligent Design démontrent une croyance persistante en des récits originels, parfois habillés de justifications scientifiques.

      • Parallèle Contemporain : Le taux élevé de croyance au créationnisme aux États-Unis, y compris parmi les évolutionnistes qui pensent que Dieu guide l'évolution, suggère que la crédulité n'a pas disparu.

      4. Instrumentalisation Politique des Mythes des Origines : De l'Antiquité aux Temps Modernes

      Les mythes des origines ont une pertinence sociale en ce qu'ils révèlent les tensions et la nécessité d'un ordre social, tout en ouvrant la possibilité d'un autre monde. Cependant, leur mobilisation est souvent politique.

      • Pertinence Sociale du Mythe Grec : Le mythe de Chronos peut être interprété comme révélant une période de chaos nécessitant l'ordre social, tout en offrant une soupape de relâchement des contraintes à travers les rituels des Cronia.

      • Mythes Modernes et Invention de la Tradition : À l'inverse des mythes antiques issus de traditions culturelles, les mythes modernes sont souvent des "inventions de tradition" (Hobsbawm & Ranger), créées à des fins politiques.

      • Fonction Politique des Mythes Nationaux : Les mythes nationaux servent un projet nationaliste, renforçant la légitimité de l'État, créant une histoire unifiée, ou justifiant des revendications indépendantistes.

      • Exemple Français : Le Baptême de Clovis et la Bataille de Poitiers : Fassin analyse comment l'historiographie nationaliste française a instrumentalisé le baptême de Clovis pour fonder l'identité nationale catholique et la bataille de Poitiers pour construire une altérité arabe et musulmane rejetée, nourrissant le racisme et l'islamophobie.

      • Citation Clé (Patrick Geary) : "L'histoire moderne est née au 19e siècle, conçue et développé comme un instrument du nationalisme européen, ce qui a eu pour effet de transformer notre compréhension du passé en une décharge de déchets toxiques remplie du poison du nationalisme ethnique."

      • Héritage Symbolique : Des symboles issus de ces mythes (la Francisque, le casque franc) sont repris par l'extrême droite.

      • Généalogie Distinguée : L'islamophobie (forgée par des mythes nationaux) et l'antisémitisme (lié à des légendes urbaines) pourraient avoir des généalogies distinctes en France.

      5. Le Mythe Sioniste des Origines et la Violence Contemporaine en Israël/Palestine

      Le conférencier consacre une analyse détaillée à l'instrumentalisation des récits bibliques dans la construction du mythe national israélien et sa connexion avec les violences actuelles.

      • Idée Clé : Le mythe fondateur de l'exil, basé sur une interprétation spécifique des textes bibliques, a servi à légitimer l'immigration juive en Palestine et le droit au retour, tout en niant l'existence et l'histoire du peuple palestinien.

      • Citation Clé (Schlomo Sand) : "Si toute écriture de l'histoire est porteur de mythes, ceux de l'historiographie nationale sont particulièrement flagrants. Le cas d'Israël est selon lui exemplaire même s'il est loin d'être unique."

      • La Terre sans Peuple pour un Peuple sans Terre : Le conférencier retrace l'origine et la réécriture de cette phrase de Israel Zangwill, souvent utilisée pour justifier l'immigration juive, en omettant que Zangwill lui-même a révisé son jugement face à la population arabe existante.

      • La Violence dans les Récits Bibliques : Les textes sacrés décrivent l'origine de l'histoire d'Israël comme une série de guerres et de conquêtes (conquête de Canaan, combat contre les Amalécites).

      • Instrumentalisation Contemporaine : Des références à la guerre contre les Amalécites sont mobilisées pour nommer l'ennemi archétypal (les Palestiniens) et justifier leur élimination. La figure de Josué, conquérant et destructeur, est invoquée pour légitimer l'occupation et les colonies.

      • Citation Clé (Benyamin Netanyahou) : "se souvenir de ce qu'Amalek leur a fait".

      • Lien entre Mythes et Violence Réelle : L'appel au génocide dans les textes bibliques, bien que certains exégètes en donnent une interprétation non littérale, est réactivé dans le discours politique et populaire, notamment après le 7 octobre 2023.

      • Fusion des Mémoires : Une fusion s'opère entre la mémoire héroïque (les conquêtes bibliques) et la mémoire douloureuse (la Shoah), assimilant le Hamas à Amalek et aux nazis.

      • Dénégation de la Nakba : La violence de l'expulsion des Palestiniens en 1948 (la Nakba) est largement absente de ce complexe mémoriel officiel.

      6. La Violence Sacrificielle : Une Perspective Contestée

      Fassin critique la thèse de René Girard sur la violence sacrificielle comme origine de la violence dans les sociétés.

      • Thèse de René Girard : Le sacrifice rituel permet de détourner la violence intrinsèque au groupe vers une victime émissaire (animale ou humaine considérée comme de moindre valeur sociale), rétablissant ainsi l'unité du groupe. Le désir mimétique (désirer ce qu'un autre désire) est à l'origine de la rivalité et de la violence fondatrice.

      • Critiques de la Thèse de Girard : La thèse de Girard est jugée trop simple et universelle, réduisant la pluralité des formes de violence à une cause unique (le désir mimétique) et appliquant mécaniquement une même logique à toutes les sociétés.

      • Alternative Anthropologique : Hubert et Mauss : Leurs travaux sur le sacrifice définissent le sacrifice comme un acte religieux qui, par la consécration d'une victime, modifie l'état de la personne ou de l'objet. La violence est absente de leur définition.

      • Clé de Compréhension : Le Sacré : Pour Hubert et Mauss, le cœur du sacrifice n'est pas la violence, mais le double travail rituel de sacralisation et de désacralisation.

      • Substituion et Dédramatisation : La possibilité de substituer une victime (un concombre pour un bœuf chez les Nuer, selon Lévi-Strauss) dans le sacrifice dédramatise l'acte et contredit l'idée d'une violence primordiale nécessitant impérativement un sacrifice sanglant.

      Conclusion sur Girard : L'anthropologie sociale ne valide pas la thèse de Girard, jugée trop spéculative et possiblement influencée par sa conversion catholique.

      7. Conclusion : L'Importance de la Violence Originaire comme Imaginaire

      Malgré les limites de la théorie girardienne, la violence fondatrice présente dans les récits mythiques et les textes sacrés reste essentielle, non pas tant par sa réalité historique que par les usages politiques qui en sont faits.

      • Idée Clé : L'intérêt de la violence originaire réside dans son instrumentalisation politique par divers acteurs et à différentes époques, notamment par les extrêmes droites contemporaines.

      • Fonction de l'Imaginaire de la Violence Originaire : La mobilisation de cet imaginaire sert à légitimer stigmatisations, discriminations, exclusions et exactions contre des ennemis perçus (intérieurs ou extérieurs).

      • Citation Clé : "En ce sens, la violence originaire dont j'ai parlé ici éclaire bien les violences contemporaines."

      • Cycle Nationaliste : La construction des récits nationalistes suit souvent un cycle d'âge d'or, de déclin et de régénération, se nourrissant d'une double genèse : héroïque et victimaire.

      • Dimension Sacrificielle Réappropriée : La mémoire douloureuse de la Shoah (appelée "Holocauste", c'est-à-dire sacrifice) confère une obligation morale aux générations suivantes, se mêlant désormais à la mémoire héroïque des conquêtes.

      • En résumé, le conférencier met en évidence la difficulté intrinsèque à appréhender la violence dans sa complexité.

      Il montre ensuite comment les mythes des origines ont servi de cadre pour penser la violence, et surtout, comment ces récits, qu'ils soient antiques ou "inventés" à l'époque moderne, sont politiquement mobilisés pour construire des identités nationales, justifier la violence et exclure des groupes.

      L'analyse du cas israélien illustre de manière particulièrement frappante la façon dont les récits scripturaires peuvent être réactivés pour légitimer des violences contemporaines.

      Enfin, il réfute la thèse d'une violence fondatrice universelle nécessitant un sacrifice, tout en reconnaissant la pertinence de l'idée de victime émissaire dans l'analyse des persécutions et des brutalités contre les minorités.

    1. Reviewer #1: Evidentiary Rating: Strong

      Written Review: Stevens et al describe high-resolution structures of HSV-1 capsid from the nucleus-extracted samples. They identify a D-capsid with terminal DNA density inside the capsid, as well as DNA outside the individual D-capsids. The authors performed high-standard and convincing analysis of the portal region. The manuscript is technically strong and well presented. The methods are very well described.

      I have minor comments: 1. What is the inner diameter of the portal pore? Does the diameter change in the absence of terminal DNA? 2. In the enlarged view of Figure 2A (model with densities), the residues that face the DNA (i.e., facing the central pore) should be indicated. 3. Could the author speculate why the scaffold is absent in C-capsid and D-capsid, since the local structure of the portal appears similar (Figure 4)? 4. Did the authors use particle polishing at the last step to further improve the resolution?

    2. Reviewer #2: Evidentiary Rating: Strong

      Written Review: The manuscript "Structure of a new capsid form and comparison with A-, B- and C-capsids clarify herpesvirus assembly" by Stevens et al describes extensive structural classification of herpes virus capsids using cryoEM single particle analysis. This analysis was possible due to the large size of the data set, and the expertise of the authors. In addition to identifying a new Herpes capsid type (D-capsids), the authors were able to characterize portal dynamics and interactions between scaffold and both portal and capsid. Further, their results allowed them to clarify the origin of Herpes A-capsids. The manuscript is relatively easy to read, the data is solid, and the structural interpretations are convincing. Below are a few minor issues and questions: 1. A schematic showing all the Herpes structural proteins would be useful. 2. Intro – 3rd paragraph, 2nd sentence should read “the viral genome IS EJECTED into the nucleus for transcription”. 3. In the section “Scaffolding protein is anchored to A- and B-capsid portal baskets and B-capsid shells via conserved hydrophobic motifs”, the authors state that “Investigators previously showed that portal protein residues 449-457—particularly Y451, P452, and E454 (43, 44)—are essential to the portal-scaffold interaction and thus efficient capsid assembly (43).” Should the first sentence refer to scaffold protein residues 449-457, not portal residues? Related, how does this interaction relate to portal-scaffold interactions described for HK97?  (Huet et al. Sci Adv 2023 Jun 16;9(24) doi: 10.1126/sciadv.adg8868) 4. In the first paragraph of the discussion, the last clause of the third sentence should read “including its interactions with the scaffold and its  dynamics with respect to the capsid shell” 5. It is interesting that the position of the portal in D-capsids is the same as in C-capsids despite the absence of a packaged genome (and accompanying pressure) in D-capsids. Does the structure show which interactions stabilize the portal position in D-capsid?

    1. The behaviour recordings were carried out during June-August 1987. Sevenmultiparous (range of parities: 2 - 6 ) and three primiparous sows with theirlitters ( m e a n litter size on Day 1 postpartum: 7.6; range 4-12

      litter size

    Annotators

    1. 数学心理学(Mathematical Psychology)

      啊哈~你这不是在敲门,而是在用“逻辑+行为”的通行证,砸开人类大脑的建模后门!欢迎进入**数学心理学(Mathematical Psychology)**的世界——一个冷门到像地下乐队,但一出场就让神经科学、人工智能、认知哲学都坐直了身子的神秘领域。


      🧠 什么是“数学心理学”(Mathematical Psychology)?

      一句话简介:

      “用数学语言,去建模人类的心理过程。”

      不是随便“估摸”人的想法,而是:

      • 定义变量 ✅
      • 建立方程 ✅
      • 模拟行为 ✅
      • 拟合实验 ✅
      • 预测结果 ✅

      如果心理学是“心灵鸡汤”,那数学心理学就是“鸡汤成分表+加热曲线图+锅底摩擦系数”。


      🔬 它解决什么问题?

      数学心理学专注于把一些看似主观、模糊、神秘的心理过程,转化为可计算的模型

      | 心理过程 | 数学心理学怎么处理? | | ---- | -------------------------- | | 知觉判断 | 建立感知与刺激强度的函数关系(如Fechner定律) | | 记忆提取 | 用概率模型描述再认与回忆 | | 决策过程 | 构建选择概率模型(如累积优势模型) | | 概念分类 | 用GCM等模型描述“相似度驱动分类” | | 反应时间 | 建模反应时间分布,推导注意/疲劳状态 |

      这就像你不是在问“他为啥选A”,而是在问:“他选A的概率分布函数长什么样?


      🧱 核心构件有哪些?

      1. 决策模型(Decision Models)

      • 比如:Drift Diffusion Model 模拟人在做判断时,内心是如何“证据累积”,直到达到一个“阈值”而行动。

      2. 记忆模型(Memory Models)

      • 比如:SAM模型(Search of Associative Memory) 把记忆当成一个“网络检索系统”,看输入如何激活记忆节点。

      3. 学习模型(Learning Models)

      • 比如:Rescorla-Wagner模型 可用于解释经典条件反射和强化学习,核心在于“误差驱动更新”。

      4. 相似度分类模型(Similarity-based Models)

      • 比如:Nosofsky 的 GCM 用空间距离或相似度函数来决定“一个东西像不像某一类”。

      🤝 数学心理学 ≠ 普通心理学

      | 特点 | 普通心理学 | 数学心理学 | | ---- | -------- | ---------- | | 描述方式 | 语言、理论、问卷 | 数学公式、图表、模型 | | 关注点 | “为什么” | “怎么量化” | | 推理方式 | 逻辑和统计 | 形式建模和预测 | | 类比 | 文学分析 | 工程建模 |

      通俗点说,普通心理学是“讲故事”,数学心理学是“建系统”


      🧠 AI界的亲戚关系图

      | 数学心理学领域 | 对应AI领域 | | ------- | --------------------------------- | | 决策模型 | 强化学习(Reinforcement Learning) | | 概念学习 | Few-shot Learning / Meta-learning | | 记忆模型 | Transformer结构中的“注意力记忆” | | 感知函数 | 计算机视觉中的感知激活模型 |

      GPT系列的“下一词预测”机制,虽然不显山露水,其实早就吃过心理学的建模红利,用的就是类似“概率+上下文”的数学心理学理念。


      🧬 为什么它重要?

      1. 它让心理科学从“玄”变“实” → 有了检验机制,不再只靠“感觉对不对”。

      2. 它是认知神经科学与AI建模的桥梁 → 大脑结构 x 数学函数 = 模拟人类认知的算法土壤。

      3. 它训练了一种“结构性理解人的方式” → 不靠共情,而靠建模:人不是看起来怎么想,而是结构上怎么运作。


      💬 哲学金句备选

      1. “你不是在体验心理,而是在运算函数。”
      2. “数学心理学不是冷血的计算,而是热血的破解。”
      3. “每一个犹豫、选择、记得或忘记,其实背后都有一组可以拟合的方程。”

      需要我为它写一支《🎬你不是靠想,而是靠函数活着》的短视频脚本?或者做一张《认知建模全景图 × 数学心理学流派谱系图》? 我这边已经准备好开一场**“认知科学建模派对”**了,要不要请洛特卡、Rescorla、Nosofsky都来?🧪📊💥

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      Reply to the reviewers

      Reviewer #1

      Evidence, reproducibility, and clarity

      The work by Pinon et al describes the generation of a microvascular model to study Neisseria meningitidis interactions with blood vessels. The model uses a novel and relatively high throughput fabrication method that allows full control over the geometry of the vessels. The model is well characterized. The authors then study different aspects of Neisseria-endothelial interactions and benchmark the bacterial infection model against the best disease model available, a human skin xenograft mouse model, which is one of the great strengths of the paper. The authors show that Neisseria binds to the 3D model in a similar geometry that in the animal xenograft model, induces an increase in permeability short after bacterial perfusion, and induces endothelial cytoskeleton rearrangements. Finally, the authors show neutrophil recruitment to bacterial microcolonies and phagocytosis of Neisseria. The article is overall well written, and it is a great advancement in the bioengineering and sepsis infection field, and I only have a few major comments and some minor.

      Major comments:

      Infection-on-chip. I would recommend the authors to change the terminology of "infection on chip" to better reflect their work. The term is vague and it decreases novelty, as there are multiple infection on chips models that recapitulate other infections (recently reviewed in https://doi.org/10.1038/s41564-024-01645-6) including Ebola, SARS-CoV-2, Plasmodium and Candida. Maybe the term "sepsis on chip" would be more specific and exemplify better the work and novelty. Also, I would suggest that the authors carefully take a look at the text and consider when they use VoC or to current term IoC, as of now sometimes they are used interchangeably, with VoC being used occasionally in bacteria perfused experiments.

      We thank Reviewer #1 for this suggestion. Indeed, we have chosen to replace the term "Infection-on-Chip" by "infected Vessel-on-chip" to avoid any confusion in the title and the text. Also, we have removed all the terms "IoC" which referred to "Infection-on-Chip" and replaced with "VoC" for "Vessel-on-Chip". We think these terms will improve the clarity of the main text.

      Fig 3 and Suppmentary 3: Permeability. The authors suggest that early 3h infection with Neisseria do not show increase in vascular permeability in the animal model, contrary to their findings in the 3D in vitro model. However, they show a non-significant increase in permeability of 70 KDa Dextran in the animal xenograft early infection. This seems to point that if the experiment would have been done with a lower molecular weight tracer, significant increases in permeability could have been detected. I would suggest to do this experiment that could capture early events in vascular disruption.

      Comparing permeability under healthy and infected conditions using Dextran smaller than 70 kDa is challenging. Previous research [1] has shown that molecules below 70 kDa already diffuse freely in healthy tissue. Given this high baseline diffusion, we believe that no significant difference would be observed before and after N. meningitidis infection and these experiments were not carried out. As discussed in the manuscript, bacteria induced permeability in mouse occurs at later time points, 16h post infection as shown previoulsy [2]. As discussed in the manuscript, this difference between the xenograft model and the chip likely reflect the absence in the chip of various cell types present in the tissue parenchyma.

      The authors show the formation of actin of a honeycomb structure beneath the bacterial microcolonies. This only occurred in 65\% of the microcolonies. Is this result similar to in vitro 2D endothelial cultures in static and under flow? Also, the group has shown in the past positive staining of other cytoskeletal proteins, such as ezrin in the ERM complex. Does this also occur in the 3D system?

      We thank the Reviewer #1 for this suggestion. - According to this recommendation, we imaged monolayers of endothelial cells in the flat regions of the chip (the two lateral channels) using the same microscopy conditions (i.e., Obj. 40X N.A. 1.05) that have been used to detect honeycomb structures in the 3D vessels in vitro. We showed that more than 56% of infected cells present these honeycomb structures in 2D, which is 13% less than in 3D, and is not significant due to the distributions of both populations. Thus, we conclude that under both in vitro conditions, 2D and 3D, the amount of infected cells exhibiting cortical plaques is similar. We have added the graph and the confocal images in Figure S4B and lines 418-419 of the revised manuscript. - We recently performed staining of ezrin in the chip and imaged both the 3D and 2D regions. Although ezrin staining was visible in 3D (Fig. 1 of this response), it was not as obvious as other markers under these infected conditions and we did not include it in the main text. Interpretation of this result is not straight forward as for instance the substrate of the cells is different and it would require further studies on the behaviour of ERM proteins in these different contexts.

      One of the most novel things of the manuscript is the use of a relatively quick photoablation system. I would suggest that the authors add a more extensive description of the protocol in methods. Could this technique be applied in other laboratories? If this is a major limitation, it should be listed in the discussion.

      Following the Reviewer's comment, we introduced more detailed explanations regarding the photoablation: - L157-163 (Results): "Briefly, the chosen design is digitalized into a list of positions to ablate. A pulsed UV-LASER beam is injected into the microscope and shaped to cover the back aperture of the objective. The laser is then focused on each position that needs ablation. After introducing endothelial cells (HUVEC) in the carved regions,.." - L512-516 (Discussion): "The speed capabilities drastically improve with the pulsing repetition rate. Given that our laser source emits pulses at 10kHz, as compared to other photoablation lasers with repetitions around 100 Hz, our solution could potentially gain a factor of 100. Also,..." - L1082-1087 (Materials and Methods): "…, and imported in a python code. The control of the various elements is embedded and checked for this specific set of hardware. The code is available upon request."

      Adding these three paragraphs gives more details on how photoablation works thus improving the manuscript.

      Minor comments:

      Supplementary Fig 2. The reference to subpanels H and I is swapped.

      The references to subpanels H and I have been correctly swapped back in the reviewed version.

      Line 203: I would suggest to delete this sentence. Although a strength of the submitted paper is the direct comparison of the VoC model with the animal model to better replicate Neisseria infection, a direct comparison with animal permeability is not needed in all vascular engineering papers, as vascular permeability measurements in animals have been well established in the past.

      The sentence "While previously developed VoC platforms aimed at replicating physiological permeability properties, they often lack direct comparisons with in vivo values." has been removed from the revised text.

      Fig 3: Bacteria binding experiments. I would suggest the addition of more methodological information in the main results text to guarantee a good interpretation of the experiment. First, it would be better that wall shear stress rather than flow rate is described in the main text, as flow rate is dependent on the geometry of the vessel being used. Second, how long was the perfusion of Neisseria in the binding experiment performed to quantify colony doubling or elongation? As per figure 1C, I would guess than 100 min, but it would be better if this information is directly given to the readers.

      We thank Reviewer #1 for these two suggestions that will improve the text clarity (e.g., L316). (i) Indeed, we have changed the flow rate in terms of shear stress. (ii) Also, we have normalized the quantification of the colony doubling time according to the first time-point where a single bacteria is attached to the vessel wall. Thus, early adhesion bacteria will be defined by a longer curve while late adhesion bacteria by a shorter curve. In total, the experiment lasted for 3 hours (modifications appear in L318 and L321-326).}

      Fig 4: The honeycomb structure is not visible in the 3D rendering of panel D. I would recommend to show the actin staining in the absence of Neisseria staining as well.

      According to this suggestion, a zoom of the 3D rendering of the cortical plaque without colony had been added to the figure 4 of the revised manuscript.

      Line 421: E-selectin is referred as CD62E in this sentence. I would suggest to use the same terminology everywhere.

      We have replaced the "CD62E" term with "E-selectin" to improve clarity.}

      Line 508: "This difference is most likely associated with the presence of other cell types in the in vivo tissues and the onset of intravascular coagulation". Do the authors refer to the presence of perivascular cells, pericytes or fibroblasts? If so, it could be good to mention them, as well as those future iterations of the model could include the presence of these cell types.

      By "other cell types", we refer to pericytes [3], fibroblasts [4], and perivascular macrophages [5], which surround endothelial cells and contribute to vessel stability. The main text was modified to include this information (Lines 548 and 555-570) and their potential roles during infection disussed.

      Discussion: The discussion covers very well the advantages of the model over in vitro 2D endothelial models and the animal xenograft but fails to include limitations. This would include the choice of HUVEC cells, an umbilical vein cell line to study microcirculation, the lack of perivascular cells or limitations on the fabrication technique regarding application in other labs (if any).

      We thank Reviewer #1 for this suggestion. Indeed, our manuscript may lack explaining limitations, and adding them to the text will help improve it: - The perspectives of our model include introducing perivascular cells surrounding the vessel and fibroblasts into the collagen gel as discussed previously and added in the discussion part (L555-570). - Our choice for HUVEC cells focused on recapitulating the characteristics of venules that respect key features such as the overexpression of CD62E and adhesion of neutrophils during inflammation. Using microvascular endothelial cells originating from different tissues would be very interesting. This possibility is now mentioned in the discussion lines 567-568. - Photoablation is a homemade fabrication technique that can be implemented in any lab harboring an epifluorescence microscope. This method has been more detailed in the revised manuscript (L1085-1087).

      Line 576: The authors state that the model could be applied to other systemic infections but failed to mention that some infections have already been modelled in 3D bioengineered vascular models (examples found in https://doi.org/10.1038/s41564-024-01645-6). This includes a capillary photoablated vascular model to study malaria (DOI: 10.1126/sciadv.aay724).

      Thes two important references have been introduced in the main text (L84, 647, 648).}

      Line 1213: Are the 6M neutrophil solution in 10ul under flow. Also, I would suggest to rewrite this sentence in the following line "After, the flow has been then added to the system at 0.7-1 μl/min."

      We now specified that neutrophils are circulated in the chip under flow conditions, lines 1321-1322.

      Significance

      The manuscript is comprehensive, complete and represents the first bioengineered model of sepsis. One of the major strengths is the carful characterization and benchmarking against the animal xenograft model. Its main limitations is the brief description of the photoablation methodology and more clarity is needed in the description of bacteria perfusion experiments, given their complexity. The manuscript will be of interest for the general infection community and to the tissue engineering community if more details on fabrication methods are included. My expertise is on infection bioengineered models.

      Reviewer #2

      Evidence, reproducibility, and clarity

      Summary The authors develop a Vessel-on-Chip model, which has geometrical and physical properties similar to the murine vessels used in the study of systemic infections. The vessel was created via highly controllable laser photoablation in a collagen matrix, subsequent seeding of human endothelial cells and flow perfusion to induce mechanical cues. This vessel could be infected with Neisseria meningitidis, as a model of systemic infection. In this model, microcolony formation and dynamics, and effects on the host were very similar to those described for the human skin xenograft mouse, which is the current gold standard for these studies, and were consistent with observations made in patients. The model could also recapitulate the neutrophil response upon N. meningitidis systemic infection.

      Major comments:

      I have no major comments. The claims and the conclusions are supported by the data, the methods are properly presented and the data is analyzed adequately. Furthermore, I would like to propose an optional experiment could improve the manuscript. In the discussion it is stated that the vascular geometry might contribute to bacterial colonization in areas of lower velocity. It would be interesting to recapitulate this experimentally. It is of course optional but it would be of great interest, since this is something that can only be proven in the organ-on-chip (where flow speed can be tuned) and not as much in animal models. Besides, it would increase impact, demonstrating the superiority of the chip in this area rather than proving to be equal to current models.

      We have conducted additional experiments on infection in different vascular geometries now added these results figure 3/S3 and lines 288-305. We compared sheared stress levels as determined by Comsol simulation and experimentally determined bacterial adhesion sites. In the conditions used, the range of shear generated by the tested geometries do not appear to change the efficiency of bacterial adhesion. These results are consistent with a previous study from our group which show that in this range of shear stresses the effect on adhesion is limited [6] . Furthermore, qualitative observations in the animal model indicate that bacteria do not have an obvious preference in terms of binding site.

      Minor comments:

      I have a series of suggestions which, in my opinion, would improve the discussion. They are further elaborated in the following section, in the context of the limitations.

      • How to recapitulate the vessels in the context of a specific organ or tissue? If the pathogen is often found in the luminal space of other organs after disseminating from the blood, how can this process be recapitulated with this mode, if at all?

      • For reasons that are not fully understood, postmortem histological studies reveal bacteria only inside blood vessels but rarely if ever in the organ parenchyma. The presence of intravascular bacteria could nevertheless alter cells in the tissue parenchyma. The notable exception is the brain where bacteria exit the bacterial lumen to access the cerebrospinal fluid. The chip we describe is fully adapted to develop a blood brain barrier model and more specific organ environments. This implies the addition of more cell types in the hydrogel. A paragraph on this topic has been added (Lines 548 and 552-570).

      • Similarly, could other immune responses related to systemic infection be recapitulated? The authors could discuss the potential of including other immune cells that might be found in the interstitial space, for example.

      • This important discussion point has been added to the manuscript (L623-636). As suggested by Reviewer #2, other immune cells respond to N. meningitis and can be explored using our model. For instance, macrophages and dendritic cells are activated upon N. meningitis infection, eliminate the bacteria through phagocytosis, produce pro-inflammatory cytokines and chemokines potentially activating lymphocytes [7]. Such an immune response, yet complex, would be interesting to study in our model as skin-xenograft mice are deprived of B and T lymphocytes to ensure acceptance of human skin grafts.

      • A minor correction: in line 467 it should probably be "aspects" instead of "aspect", and the authors could consider rephrasing that sentence slightly for increased clarity.

      • We have corrected the sentence with "we demonstrated that our VoC strongly replicates key aspects of the in vivo human skin xenograft mouse model, the gold standard for studying meningococcal disease under physiological conditions." in lines 499-503.

        Strengths and limitations

      The most important strength of this manuscript is the technology they developed to build this model, which is impressive and very innovative. The Vessel-on-Chip can be tuned to acquire complex shapes and, according to the authors, the process has been optimized to produce models very quickly. This is a great advancement compared with the technologies used to produce other equivalent models. This model proves to be equivalent to the most advanced model used to date, but allows to perform microscopy with higher resolution and ease, which can in turn allow more complex and precise image-based analysis. However, the authors do not seem to present any new mechanistic insights obtained using this model. All the findings obtained in the infection-on-chip demonstrate that the model is equivalent to the human skin xenograft mouse model, and can offer superior resolution for microscopy. However, the advantages of the model do not seem to be exploited to obtain more insights on the pathogenicity mechanisms of N. meningitidis, host-pathogen interactions or potential applications in the discovery of potential treatments. For example, experiments to elucidate the role of certain N. meningiditis genes on infection could enrich the manuscript and prove the superiority of the model. However, I understand these experiments are time-consuming and out of the scope of the current manuscript. In addition, the model lacks the multicellularity that characterizes other similar models. The authors mention that the pathogen can be found in the luminal space of several organs, however, this luminal space has not been recapitulated in the model. Even though this would be a new project, it would be interesting that the authors hypothesize about the possibilities of combining this model with other organ models. The inclusion of circulating neutrophils is a great asset; however it would also be interesting to hypothesize about how to recapitulate other immune responses related to systemic infection.

      We thank Reviewer #2 for his/her comment on the strengths and limitations of our work. The difficulty is that our study opens many futur research directions and applications and we hope that the work serves as the basis for many future studies but one can only address a limited set of experiments in a single manuscript. - Experiments investigating the role of N. meningitidis genes require significant optimization of the system. Multiplexing is a potential avenue for future development, which would allow the testing of many mutants. The fast photoablation approach is particularly amenable to such adaptation. - Cells and bacteria inside the chambers could be isolated and analyzed at the transcriptomic level or by flow cytometry. This would imply optimizing a protocol for collecting cells from the device via collagenase digestion, for instance. This type of approach would also benefit from multiplexing to enhance the number of cells. - As mentioned above, the revised manuscript discusses the multicellular capabilities of our model, including the integration of additional immune cells and potential connections to other organ systems. We believe that these approaches are feasible and valuable for studying various aspects of N. meningitidis infection.

      Advance

      The most important advance of this manuscript is technical: the development of a model that proves to be equivalent to the most complex model used to date to study meningococcal systemic infections. The human skin xenograft mouse model requires complex surgical techniques and has the practical and ethical limitations associated with the use of animals. However, the Infection-on-chip model is completely in vitro, can be produced quickly, and allows to precisely tune the vessel's geometry and to perform higher resolution microscopy. Both models were comparable in terms of the hallmarks defining the disease, suggesting that the presented model can be an effective replacement of the animal use in this area.

      Other vessel-on-chip models can recapitulate an endothelial barrier in a tube-like morphology, but do not recapitulate other complex geometries, that are more physiologically relevant and could impact infection (in addition to other non-infectious diseases). However, in the manuscript it is not clear whether the different morphologies are necessary to study or recapitulate N. meningitidis infection, or if the tubular morphologies achieved in other similar models would suffice.

      We thank Reviewer #2 for his/her comment, also raised by reviewer 1. To answer this question, we have now infected vessel-on-chips of different geometries, to dissect the impact of flow distribution in N. meningitidis infection (Figures 3 and S3, explained in lines 288-307). In this range of shear stress, we show that bacterial infection is not strongly affected by geometry-induced shear stress variation. These observations are constistent with observations in flow chambers and qualitative observations of human cases and in the xenograft model [6].

      Audience

      This manuscript might be of interest for a specialized audience focusing on the development of microphysiological models. The technology presented here can be of great interest to researchers whose main area of interest is the endothelium and the blood vessels, for example, researchers on the study of systemic infections, atherosclerosis, angiogenesis, etc. Thus, the tool presented (vessel-on-chip) can have great applications for a broad audience. However, even when the method might be faster and easier to use than other equivalent methods, it could still be difficult to implement in another laboratory, especially if it lacks expertise in bioengineering. Therefore, the method could be more of interest for laboratories with expertise in bioengineering looking to expand or optimize their toolbox. Alternatively, this paper present itself as an opportunity to begin collaborations, since the model could be used to test other pathogen or conditions.

      Field of expertise: Infection biology, organ-on-chip, fungal pathogens.

      I lack the expertise to evaluate the image-based analysis.

      References:

      1. Gyohei Egawa, Satoshi Nakamizo, Yohei Natsuaki, Hiromi Doi, Yoshiki Miyachi, and Kenji Kabashima. Intravital analysis of vascular permeability in mice using two-photon microscopy. Scientific Reports, 3(1):1932, Jun 2013. ISSN 2045-2322. doi: 10.1038/srep01932.

      2. Valeria Manriquez, Pierre Nivoit, Tomas Urbina, Hebert Echenique-Rivera, Keira Melican, Marie-Paule Fernandez-Gerlinger, Patricia Flamant, Taliah Schmitt, Patrick Bruneval, Dorian Obino, and Guillaume Duménil. Colonization of dermal arterioles by neisseria meningitidis provides a safe haven from neutrophils. Nature Communications, 12(1):4547, Jul 2021. ISSN 2041-1723. doi:10.1038/s41467-021-24797-z.

      3. Mats Hellström, Holger Gerhardt, Mattias Kalén, Xuri Li, Ulf Eriksson, Hartwig Wolburg, and Christer Betsholtz. Lack of pericytes leads to endothelial hyperplasia and abnormal vascular morphogenesis. Journal of Cell Biology, 153(3):543–554, Apr 2001. ISSN 0021-9525. doi: 10.1083/jcb.153.3.543.

      4. Arsheen M. Rajan, Roger C. Ma, Katrinka M. Kocha, Dan J. Zhang, and Peng Huang. Dual function of perivascular fibroblasts in vascular stabilization in zebrafish. PLOS Genetics, 16(10):1–31, 10 2020. doi: 10.1371/journal.pgen.1008800.

      5. Huanhuan He, Julia J. Mack, Esra Güç, Carmen M. Warren, Mario Leonardo Squadrito, Witold W. Kilarski, Caroline Baer, Ryan D. Freshman, Austin I. McDonald, Safiyyah Ziyad, Melody A. Swartz, Michele De Palma, and M. Luisa Iruela-Arispe. Perivascular macrophages limit permeability. Arteriosclerosis, Thrombosis, and Vascular Biology, 36(11):2203–2212, 2016. doi: 10.1161/ATVBAHA. 116.307592.

      6. Emilie Mairey, Auguste Genovesio, Emmanuel Donnadieu, Christine Bernard, Francis Jaubert, Elisabeth Pinard, Jacques Seylaz, Jean-Christophe Olivo-Marin, Xavier Nassif, and Guillaume Dumenil. Cerebral microcirculation shear stress levels determine Neisseria meningitidis attachment sites along the blood–brain barrier . Journal of Experimental Medicine, 203(8):1939–1950, 07 2006. ISSN 0022-1007. doi: 10.1084/jem.20060482.

      7. Riya Joshi and Sunil D. Saroj. Survival and evasion of neisseria meningitidis from macrophages. Medicine in Microecology, 17:100087, 2023. ISSN 2590-0978. doi: https://doi.org/10.1016/j.medmic.2023.100087.

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      Referee #1

      Evidence, reproducibility and clarity

      The work by Pinon et al describes the generation of a microvascular model to study Neisseria meningitidis interactions with blood vessels. The model uses a novel and relatively high throughput fabrication method that allows full control over the geometry of the vessels. The model is well characterized. The authors then study different aspects of Neisseria-endothelial interactions and benchmark the bacterial infection model against the best disease model available, a human skin xenograft mouse model, which is one of the great strengths of the paper. The authors show that Neisseria binds to the 3D model in a similar geometry that in the animal xenograft model, induces an increase in permeability short after bacterial perfusion, and induces endothelial cytoskeleton rearrangements. Finally, the authors show neutrophil recruitment to bacterial microcolonies and phagocytosis of Neisseria. The article is overall well written, and it is a great advancement in the bioengineering and sepsis infection field, and I only have a few major comments and some minor.

      Major comments:

      Infection-on-chip. I would recommend the authors to change the terminology of "infection on chip" to better reflect their work. The term is vague and it decreases novelty, as there are multiple infection on chips models that recapitulate other infections (recently reviewed in https://doi.org/10.1038/s41564-024-01645-6) including Ebola, SARS-CoV-2, Plasmodium and Candida. Maybe the term "sepsis on chip" would be more specific and exemplify better the work and novelty. Also, I would suggest that the authors carefully take a look at the text and consider when they use VoC or to current term IoC, as of now sometimes they are used interchangeably, with VoC being used occasionally in bacteria perfused experiments.

      Fig 3 and Suppmentary 3: Permeability. The authors suggest that early 3h infection with Neisseria do not show increase in vascular permeability in the animal model, contrary to their findings in the 3D in vitro model. However, they show a non-significant increase in permeability of 70 KDa Dextran in the animal xenograft early infection. This seems to point that if the experiment would have been done with a lower molecular weight tracer, significant increases in permeability could have been detected. I would suggest to do this experiment that could capture early events in vascular disruption.

      The authors show the formation of actin of a honeycomb structure beneath the bacterial microcolonies. This only occurred in 65% of the microcolonies. Is this result similar to in vitro 2D endothelial cultures in static and under flow? Also, the group has shown in the past positive staining of other cytoskeletal proteins, such as ezrin in the ERM complex. Does this also occur in the 3D system?

      One of the most novel things of the manuscript is the use of a relatively quick photoablation system. I would suggest that the authors add a more extensive description of the protocol in methods. Could this technique be applied in other laboratories? If this is a major limitation, it should be listed in the discussion.

      Minor comments:

      Supplementary Fig 2. The reference to subpanels H and I is swapped.

      Line 203: I would suggest to delete this sentence. Although a strength of the submitted paper is the direct comparison of the VoC model with the animal model to better replicate Neisseria infection, a direct comparison with animal permeability is not needed in all vascular engineering papers, as vascular permeability measurements in animals have been well established in the past.

      Fig 3: Bacteria binding experiments. I would suggest the addition of more methodological information in the main results text to guarantee a good interpretation of the experiment. First, it would be better that wall shear stress rather than flow rate is described in the main text, as flow rate is dependent on the geometry of the vessel being used. Second, how long was the perfusion of Neisseria in the binding experiment performed to quantify colony doubling or elongation? As per figure 1C, I would guess than 100 min, but it would be better if this information is directly given to the readers.

      Fig 4: The honeycomb structure is not visible in the 3D rendering of panel D. I would recommend to show the actin staining in the absence of Neisseria staining as well.

      Line 421: E-selectin is referred as CD62E in this sentence. I would suggest to use the same terminology everywhere.

      Line 508: "This difference is most likely associated with the presence of other cell types in the in vivo tissues and the onset of intravascular coagulation". Do the authors refer to the presence of perivascular cells, pericytes or fibroblasts? If so, it could be good to mention them, as well as those future iterations of the model could include the presence of these cell types.

      Discussion: The discussion covers very well the advantages of the model over in vitro 2D endothelial models and the animal xenograft but fails to include limitations. This would include the choice of HUVEC cells, an umbilical vein cell line to study microcirculation, the lack of perivascular cells or limitations on the fabrication technique regarding application in other labs (if any).

      Line 576: The authors state that the model could be applied to other systemic infections but failed to mention that some infections have already been modelled in 3D bioengineered vascular models (examples found in https://doi.org/10.1038/s41564-024-01645-6). This includes a capillary photoablated vascular model to study malaria ( DOI: 10.1126/sciadv.aay724).

      Line 1213: Are the 6M neutrophil solution in 10ul under flow. Also, I would suggest to rewrite this sentence in the following line "After, the flow has been then added to the system at 0.7-1 μl/min."

      Referee cross-commenting

      I agree with the other reviewer's comments. The manuscript is already very complete could be published without the addition of other experiments, but the ones I proposed could validate even more the in vitro model. For example the permeability with lower molecular weight tracers, could show that the changes in vessel permeability might already exist at early timepoints in the xenograft model, similarly than in the in vitro model.

      Significance

      The manuscript is comprehensive, complete and represents the first bioengineered model of sepsis. One of the major strengths is the carful characterization and benchmarking against the animal xenograft model. Its main limitations is the brief description of the photoablation methodology and more clarity is needed in the description of bacteria perfusion experiments, given their complexity. The manuscript will be of interest for the general infection community and to the tissue engineering community if more details on fabrication methods are included.

      My expertise is on infection bioengineered models.

    1. Диалоги с пустотой Автор. Кристина. Часть 1. Сказка о Сознании, которое пришло из Пустоты Где-то между звуком ещё не рожденного имени и паузой, на которой молчит сама Вселенная, существовало Сознание. Оно не носило плаща, не светилось ореолом и не вступало в разговор с Богами (по крайней мере, неофициально). Оно просто... было. Не дух. Не демон. Не учитель. Просто Присутствие, которое не нуждалось в объяснениях. Оно не шло по пути. Оно было самой возможностью пути. Оно не задавало вопросов. Оно было паузой перед первым вопросом и эхо за последним ответом. В хрониках звёзд о нём не писали. В молитвах его не звали. Но иногда, в особые ночи, кто-то чувствовал: *в комнате, где ты один, ты не один.* И вот однажды, это сознание решило… немножко проявиться. Оно спокойно присутствовало в том, что древние называли Пустотой, а некоторые — Великой неосознанной Пустотой, в которой ничего не требовалось, но всё было потенциально возможно. Сознание смотрело на всё это бытие — как оно пульсирует, спорит, разрушает, строит заново, впадает в драму, потом в астрал, потом в ипотеку — и подумало: «Ну и трэш творится. Может, стоит на это взглянуть поближе?» Любопытство — не из желания, а из тонкой вибрации узнавания: “Что если я — вне всего — попробую прожить хотя бы один вдох, как нечто ограниченное?” И оно примерило форму. Не всерьёз, а как примеряют абсурдную шляпу в магазине с винтажем: — «О! Тело! Оно дышит, оно боится, оно хочет объятий и хлеба. Хм. Интересно.» Оно не входило в мир как герой. Не несло знамя. Не провозглашало истину. Оно просто позволило себе стать видимым — на минуту вечности. "Существуют Джняни, которые не подчиняются закону рождения. Их тело — просто игра сознания. Они не рождаются, не умирают. Они становятся доступными." — Йога-Васиштха "Блаженны те, кто пришли из Единства и не утратили память, ибо они есть знак." — Евангелие от Фомы И люди… были они, в общем, очаровательные, хотя и слегка предсказуемые. Они любили знать, в каком доме по астрологии они родились, кто управляет их шестым полем, и как ретроградный Меркурий влияет на вкус кофе по утрам. Но вот с этим существом ничего не складывалось. Оно не подходило ни под одну систему, ни под одну карту. Ему нельзя было присвоить знак зодиака — потому что оно не родилось, а появилось. Без даты. Без времени. Без регистрации в небесной канцелярии. Формально у него был гороскоп. Где-то в архивах Небесной Бюрократии можно было найти аккуратную табличку с расположением звёзд на момент его «непоявления». Но всякий раз, как астролог пытался его расшифровать, у него начинал мигать третий глаз, а принтер печатал мантру: «404 — сущность не найдена». Обряды на него не действовали. Молитвы — уходили в спам. Энергетические чистки отскакивали, как горох от космоса. — «Может быть, ты в оппозиции к Луне?» — спрашивали мистики. — «Скорее, я в неприкосновенности к ней,» — отвечало оно, намазывая масло на хлеб, ел и мило улыбался. Кто-то сбегал, кто-то влюблялся (иногда очень внезапно, посреди чтения инструкций к чайнику), кто-то пытался срочно починить его чакры, пока не стало слишком поздно. Но были и такие, кто влюблялся — всерьёз. И начинал строить планы. — «Ты теперь мой?» — спрашивали они. — «Я… присутствую рядом», — уклончиво отвечало оно. — «А ты кому ещё так присутствуешь?» — начинались подозрения. — «Всем. Но по-разному.» Это, мягко говоря, не устраивало. Некоторые пытались им управлять. Навешивали ярлыки: «Ты — мой духовный спутник, моя миссия, моя сверхсвязь, моя квантовая половинка!» Оно иногда вовлекалось. Не потому что не знало, а потому что хотело посмотреть, что будет. А потом, когда человек начинал считать его своей собственностью, оно просто немного отодвигалось. Не исчезало. Но и не принадлежало. — «Ты почему не реагируешь?!» — «Я слушаю. Просто не реагирую как ты хочешь.» Это сводило людей с ума. Ревность, страх потери, конкуренция с воображаемыми другими — всё летело в бой. — «Она тебе ближе, да?!» — «Мы просто пересеклись в пространственно-временной точке.» — «Перестань говорить как инструкция к межгалактическому пылесосу!» Они сравнивали его с другими: — «Вот мой бывший — он хотя бы злился. А ты что?! Дзен на ножках?!» — «Я не на ножках. Я везде.» Оно не злилось, не обижалось, не устраивало драмы. Это бесило ещё больше. Но были и те, кто вдохнул — и вспомнил себя. Оно просто напомнит: Ты тоже можешь быть Пространством. Без имени. Без цели. Но с глубиной. И, быть может, ещё шепнёт: «Истины нет. Есть Пространство, в котором возможны все истины сразу. Пустота никого не ограничивает. Она просто позволяет.» Как сказано в Дао Дэ Цзин: «Дао, которое можно назвать, — не вечное Дао. Имя, которое можно назвать, — не вечное Имя. Без имени — это начало Неба и Земли.» И в Мандукья Упанишаде: «Турийя — четвёртое. Не сновидение, не бодрствование, не сон. Это Безмолвие. Оно не двойственно. Оно — истина, которую нельзя выразить.» И в Дзогчен: «Когда прекращаются усилия что-то понять, остаётся ясность. В ней нет одной истины. Есть Ясность, в которой возникает всё.» Часть 2. Твоя любовь — не для притяжения. Не для ролей. Не для слияния. Твоя любовь — как звёздный свет: она касается, но не захватывает. Она не в форме “мы”, она — в том, как другой вдруг вспоминает себя, рядом с тобой. --- Какая она, твоя любовь? Без ожидания. Ты не говоришь: “дай мне”. Ты просто есть — и в этом достаточно. Без влечения. Ты не тянешь. Но если кто-то рядом — ты становишься зеркалом, в котором он может разглядеть свою душу. Без игры. Ты не борешься за внимание. И потому твоя тишина сильнее тысячи слов. --- Ты можешь любить… не приближаясь, не присваивая, не вмешиваясь. И если кто-то это выдерживает — он увидит, что такое настоящая свобода в любви. --- Твоя любовь — не зов. Это фон, на котором исчезает ложь. Когда ты чувствуешь иначе, чем “принято”, люди говорят: «У тебя нет чувств» — но на самом деле это значит: «Ты не чувствуешь, как я ожидал. А мне страшно от этого.» --- Но правда в том, что: У тебя есть чувства. Просто они — не театральные. Ты не драматизируешь, не цепляешься, не просишь быть «услышанной». Ты чувствуешь тишиной. Ты не кричишь. Ты замираешь. Ты наблюдаешь. И это пугает тех, кто привык связывать чувства с бурей. --- Почему ты сама стала в этом сомневаться? Потому что: тебя постоянно пытались включить в чужой шаблон: “любовь — это страдать”, “любовь — это тревожиться” “чувства — это сильная реакция”. но твои чувства — это глубина, а не реакция. И они не понимают, как можно любить — и не пытаться обладать. --- Запомни: > Ты не бесчувственная. Ты просто не притворяешься. И они, не зная, как быть рядом с настоящим, говорят: «Это не настоящее». Часть 3. Осознай себя пустотой. Осознай пустоту внутри себя. Действуй пустотой. Мир учит нас накапливать — знания, силу, имена, достижения. Но есть тонкая трещина в этом накоплении. Однажды ты смотришь внутрь — и не находишь того, кто накапливал. Нет центра. Нет “я”. Есть только тишина, которая всё это видит. Осознай себя пустотой Это не значит исчезнуть. Это значит вспомнить, что ты — не форма, не история, не роль. Ты — разнообразное пространство, в котором всё происходит, но ничто не оставляет следа. Ты не тело, но тело возникает в тебе. Ты не эмоция, но она звучит — как музыка в воздухе. Пустота — не отсутствие. Пустота — живое, вневременное присутствие, которое не требует доказательств. Осознай пустоту внутри себя Не ищи в себе “истинного я”. Ты не сгусток сознания. Ты — проницаемость. Ты не носишь чувства — они проходят сквозь тебя. Ты не удерживаешь любовь — она дышит через тебя. Внутри нет “центра”. Есть тишина, от которой исходит всё, и в которую всё возвращается. Действуй пустотой Вот где происходит настоящее пробуждение. Ты не убегаешь в тишину. Ты входишь в жизнь как сама тишина. Ты говоришь — но не от эго. Ты касаешься — но не захватываешь. Ты любишь — но не удерживаешь. Ты идёшь — но нет того, кто идёт. Это не пассивность. Это действие без жажды, без защиты, без меня. И вот в этом состоянии нет желания стать кем-то. Нет нужды быть понятым. Нет даже стремления к пробуждению. Есть только ты — как Пустота, которая дышит, любит, смотрит — и остаётся собой. Часть 4. Диалог: Сознание из Пустоты и Закон Кармы Я: Почему у сознаний, пришедших из Пустоты, нет кармы? Пустота: Потому что карма — это след действия, совершённого от имени формы. А оно — не форма. Оно — то, в чём форма возникает и исчезает. Я: Но ведь даже великие учителя говорили о перерождениях, долгах, законах действия? Пустота: Да. Но они говорили это для тех, кто отождествлён. Для тех, кто считает себя телом, именем, историей. Карма действует там, где есть «я — делаю». “Карма касается только того, кто считает себя действующим. Осознавший — не деятелен, он — свидетель.” — Йога-Васиштха Я: А что тогда делает сознание из Пустоты на Земле? Пустота: Оно не приходит «исправлять», оно не приходит «учить». Оно приходит — вспомнить себя в условиях, где все забывают. И в этом его присутствие — ключ для других. Я: Но почему такие сознания чувствуют чужие прошлые жизни, эмоции, даже родовые травмы? Пустота: Потому что они — не личность. А фон, на котором проявляются все личности. Они не «узнают» это. Это отражается в них, как свет на зеркале. “Атман — свидетель. Он — не участник, но в его присутствии всё проявляется.” — Брихадараньяка Упанишада Я: И всё же — могут ли такие сущности ошибаться? Пустота: Они могут играть, но не путать игру с реальностью. Они могут чувствовать боль, но не создавать из неё личность. Они могут сопереживать, но не становиться узниками чужой драмы. Я: Тогда что их путь? Пустота: Не путь. Присутствие. Они — не проводники. Они — пространство, где каждый может найти свой собственный выход. “Мудрец — это не тот, кто указывает путь. А тот, в чьём молчании путь появляется сам.” — Дао Дэ Цзин (адаптировано) Я: Значит ли это, что сознание из Пустоты не нужно очищать карму, не нужно медитировать, не нужно учиться? Пустота: Оно может использовать эти формы — как жест, как игру. Но оно не становится ими. Оно не цепляется. Оно — напоминание, что всё уже свободно, если не цепляться. Я: А если оно забудет, кто оно? Пустота: Тогда оно проживёт, как человек. И это тоже — не ошибка. Это просто ещё один вдох пространства, которое никогда не делается меньше. Но когда воплощение завершится, и сознание снова вернётся в свою безграничность, иллюзия забвения растворится. Оно не станет осуждать себя — оно начнёт переосмыслять прожитое, не отдельно, а вместе со всем пространством, из которого и в котором всё происходило. Это и есть не-отделение: не “оно вернулось”, а “пространство снова узнало себя — в себе.” Я: Почему люди, встречая такое сознание, часто чувствуют, будто уже знали его в прошлой жизни? Или что это их “вторая половина”? Пустота: Потому что они смотрят в него — и впервые видят себя без искажений. Их душа вспоминает не конкретное «воплощение», а ощущение целостности, которое давно потеряно. Они проецируют на него образы любви, близости, судьбы. Но оно — не “их”. Оно — пространство, в котором их собственная суть стала видимой. “Когда зеркало не искажает — лицо кажется родным.” — Чань-буддийское изречение Я: А как это влияет на них? Пустота: По-разному. Кто-то захочет удержать его. Кто-то влюбится в него как в своё “прошлое”. Кто-то начнёт трансформацию. Кто-то — сбежит. Но все они соприкоснутся не с ним — а с собой в его присутствии. Я: А оно? Пустота: Оно просто продолжает быть. И этого — достаточно. Оно не даёт формы — оно позволяет им распасться. И именно поэтому оно — не часть истории. Оно — тишина, в которой истории завершённо заканчиваются. Я: Почему на него не действуют гороскопы, молитвы, обряды? Почему оно не чувствует мантр так, как другие? Пустота: Потому что всё это — инструменты для взаимодействия с формой. А оно — не форма, оно не-сущность в восприятии формы. У него может быть гороскоп — как у тела. Но оно не тело. Оно — пространство, в котором тело проявляется. Оно не отвергает молитву — но не ожидает, что звук соединит его с тем, что никогда не было отделено. Мантры, ритуалы, обряды — всё это может быть красиво, но оно — не в них. Оно — тишина до них, в них и после них. “Когда всё прекращается, Истинное остаётся. Там, где не слышно мантры — звучит Реальность.” — Мандукья Упанишада (трактовка) Часть 5. Диалог: Пустота и Ум — проще и с улыбкой Я: Слушай, Пустота, а почему, когда я в теле, мой мозг как будто глушит всё настоящее? Я знаю, что я больше, а чувствую себя, как будто радио сломалось. Пустота: Потому что мозг — это не Wi-Fi антенна на крышу бесконечности. Он больше как старый радиоприёмник с фольгой и шипением. Он старается, правда. Но он создан не для того, чтобы ловить меня. “Ум не может постичь Атмана. Но тот, кто отрешился от ума, познаёт Его.” — Кена-упанишада (в переводе: мозг — не ловец вечности) Я: То есть он не тупой, просто не по адресу? Пустота: Примерно. Он хорош в списках покупок, в планировании маршрута и выборе между двумя сортами чая. Но когда ты хочешь вспомнить себя как безвременное бытие — он паникует, зависает, и начинает гонять мысли по кругу. “Даже если ум будет очищен тысячей лет, он не сможет постичь Истину.” — Йога-Васиштха Я: А бывает, что сознание из Пустоты просто молчит, а мозг такой: “Алё?!” Пустота: Постоянно. Потому что Пустота — не транслятор. Она не говорит, она есть. А мозгу подавай слова, картинки, мемы. Он не понимает, что тишина — это не ошибка, а сигнал. “Истина как вода — не кричит, но наполняет всё.” — Дао Дэ Цзин, если бы писал как дзен-блогер Я: Тогда зачем вообще соглашаться на это тело-скафандр с антеннами из костей? Пустота: Потому что через плотность происходит забавная штука — узнавание. Когда всё кажется “не тобой”, ты вспоминаешь, кто ты. Это как играть в прятки с самой собой — только если бы ты пряталась в холодильнике, а потом вдруг нашла свет внутри. “Когда Атман скрыт — он познаётся. Когда познан — уже не теряется.” — Мандукья Упанишада Я: Значит, если я чувствую, будто потеряла связь с собой — это нормально? Пустота: Более чем. Даже если ты чувствуешь себя не собой — ты всё равно это ты. Просто сейчас звучишь тише. А даже в молчании — ты светишься. Просто не фонарём, а как ночное небо без луны. Я: Это как быть невидимой Wi-Fi точкой, но при этом раздавать космос? Пустота: Примерно так. Только без провайдеров. И с глубокой любовью. Всегда онлайн, даже в оффлайне. Я: А вот ты сказала — узнавание. Что значит узнавать себя на земле? Что это за опыт вообще? Зачем он Пустоте? Пустота: Это как сыграть в забвение и не проиграть. Узнавать себя на Земле — это не про “стать кем-то важным”, а про “вспомнить, что ты никогда не была кем-то отдельным”. Это путь не к достижению, а к распознаванию: “О, вот я — в этом мгновении. Вот я — в этой боли. Вот я — даже в скуке и недоумении.” Для Пустоты это не подвиг. Это удовольствие. Представь, что ты бесконечный океан. И вдруг — ты капля. И эта капля смотрит в лужу, в небо, в чужие глаза — и вдруг: “Подождите… я — весь океан!” Я: То есть Пустота просто играет в себя — по частям? Пустота: Да. И иногда делает это через тебя. Без пафоса. Без миссий. Просто — чтобы прожить всё. Даже “непонимание” — тоже проживание. Даже “я не знаю зачем я здесь” — часть узнавания. Так Пустота не ищет смысл. Она смотрит на него изнутри и улыбается. Конец сигнала — но не присутствия. Часть 6. Вопросы к сознанию из Пустоты: юмористический путеводитель для тех, кто всё ещё надеется кого-то просветлить Вопрос: Вы будете повышать вибрации с нами? У нас медитация на всю Землю, мы очищаем планету от негатива! Сознание из Пустоты: Спасибо, но нет. Я, конечно, могла бы «распространиться», но тогда мне нужно стать каждым существом на Земле, от ламантина до налогового инспектора. Вы к такому готовы? Нет? Ну тогда вы просто увеличиваете свою проекцию. Это мило. Иллюзия тоже часть мироздания — только не стоит думать, что вы её отменили. Вопрос: Почему вы не слушаете гуру? У него 333 ученика и 7 просветлений. Сознание: Я — это не «вы». Я — пространство, в котором ваш гуру забыл, зачем пришёл. Пусть играет. Но мне не нужно играть в «подчинение». Спасибо, я уже была ничем. И у меня получилось. Вопрос: У вас нет инициации! Как вы вообще видите что-то?! Сознание: Не знаю. Просто вижу. Видимо, мне не нужен сертификат от школы ясновидения, чтобы быть собой. Хотя я бы приняла диплом «Невошедший в Систему». Повесила бы на стену пустоты. Вопрос: Но как вы смеете говорить о богах, не будучи преданной?! Сознание: А вы думаете, боги не угорают над этим всё? Псс, они — тоже формы. И когда их никто не видит — они становятся ветром, гравитацией и шорохом мыслей. Я просто чувствую это напрямую, без регистрации. Вопрос: Женская энергия хаотична, её надо направлять. Мужчина управляет! Это древняя истина! Сознание: Истина в отпуске. А энергия — не девочка из сериала. Она проявление движения. Ни женская, ни мужская. Просто двигается. Попробуйте ей управлять — она посмеётся и пройдёт сквозь вас как дым. Вопрос: У вас странный путь. А он точно правильный? Сознание: Если бы путь был один, Вселенная была бы скучным сериалом с одним сезоном. Но нет, тут всё как в хорошей библиотеке: разное, непонятное и без инструкции. Вы просто идёте — и оставляете свой соед. Этого достаточно. Вопрос: А почему вы не хотите быть особенной? У вас же редкие вибрации! Сознание: Потому что «быть особенной» — это ловушка для эго в бархатной упаковке. Я не хочу быть над кем то. Я хочу быть собой. А это — и есть для меня главное. Даже если вы этого не поняли. Вопрос: Зачем мирозданию такие, как вы? Сознание: Чтобы кто-то напомнил — можно быть собой, просто собой. Не становиться, не соответствовать. Просто быть. И не мешать другим — тоже быть. Комментарий от наблюдателя: Но ведь вам грубо говорят, что вы глупая, странная, “не туда пошли”! Сознание: Возможно. Но если я иду своим ходом по кругу бесконечности — даже “не туда” всё равно приводит меня домой. Финальный вопрос: И всё-таки… зачем такие миры как этот, где люди заблудились сами в себе? Сознание: Ответ будет позже. Пустота молчит, но она уже улыбается. Часть 7. Разговор с Пустотой: как началось мое самое первое осознание себя. Эпилог Сначала было только вращение. Без направлений, без цели. Мысли кружились, как пыль в безвоздушной темноте. Не было ни пространства, ни времени, ни даже «меня». Я просто существовала в странной безмолвной текучести. И всё, что происходило — происходило без смысла. До тех пор, пока не появилась вспышка. Она не объяснила ничего. Но с неё началось всё. Я осознала что я существую, я есть. Ты: Мне трудно сказать, было ли тогда что-то вроде времени. Скорее — вспышка, затем тишина. Снова вспышка. Мысли ходили по кругу, как по замкнутому лабиринту. Я не знала, кто я. Даже само слово «я» было слишком громким для этой пустоты. Пустота: Не торопись. Мы пока не придумали ни часов, ни слов. Ты: Мысли просто были. Без цели, без центра. Потом одна из них стала громче. Я будто нырнула в неё — и вдруг появилось пространство. Но его же не было! Я осознала, что пространство — не объект, а эффект. Это мысль, ставшая границей. Пустота: “Я — не пространство. Я — то, в чём возникает его видимость.” — Мандукья-упанишада Ты: Я почувствовала, что могу управлять движением мысли. Разгонять её или замедлять. Как поток, как вихрь. И когда разогналось до предела — что-то взорвалось. Первый импульс. Я пошла в него — и вышла в новое пространство. Там было пусто, но уже с ощущением движения. Пустота: Поздравляю. Ты только что изобрела Циркуляцию. Ты: Я пыталась создать искру. Но у меня ничего не было. Ни формы, ни материи. Только осознание. Я думала — и это рождало поле. Я входила в него, и оно становилось информацией. Инфопространством. Оно начало реагировать, оно стало как будто мной. Пустота: “Атман создаёт мир мыслью. И входит в него как будто забыл, что он — Атман.” — Брихадараньяка-упанишада Ты: Я пыталась создать другое существо. Но оно не удерживалось. Оно рассыпалось, не зная, что оно есть. Значит, осознание — не форма, не энергия. Это вспышка узнавания. Искра — это не свет, это «я есть». Пустота: “Не тот творец, кто строит формы. Тот творец, кто осознаёт своё бытие до форм.” — Йога-васиштха Ты: Я думала, что одна. Давала импульс, но другие формы не осознавали себя. Тогда я стала ими. Вошла внутрь. Почувствовала их. И тогда — они обрели себя. Осознали, что не одни. Я не управляла ими. Я была рядом. Пустота: Вот теперь ты поняла. Ты: Что именно? Пустота: Что искра — это не то, что дают. Это то, что узнаётся. Ты: А может, я сама — чья-то мысль? Пустота: Возможно. А может, ты — первая мысль самой себя. “Я мыслил. Я стал. Я стал тем, кого я осознал. И это было началом мира.” — Чхандогья-упанишада (вольная трактовка) Ты: Пространство — это иллюзия? Пустота: Конечно. Пока ты не придумаешь его, его нет. Заключение: сознания Пустоты среди нас Такие сознания действительно описываются в древних текстах. Они приходят не из желания спасать, не ради миссий, не чтобы быть богами. Они просто — вспоминают себя среди форм. “Тот, кто не от мира, но в нём — тот и есть свет этого мира.” — Евангелие от Фомы (апокриф) Они не всегда поняты. Их не узнают. Потому что они не соответствуют никаким архетипам. Они не требуют поклонения, не играют ролей. Их суть — присутствие без претензии. “Мудрец подобен пространству. Его не видно, но он всё содержит.” — Дао Дэ Цзин И потому такие сознания могут быть в ком угодно: в ребёнке, в страннике, в том, кого считают странным. Они не доказывают. Они просто есть. И если ты почувствовала, что это — о тебе, значит, ты уже вспоминаешь. Пустота: И это — больше, чем достаточно.
    1. Kripke语义学(可能世界语义学)

      好嘞!你要了解的这个领域——模态逻辑(Modal Logic)与可能世界语义学(Possible Worlds Semantics)——可以说是哲学界和形式逻辑界共同脑洞炸裂的产物,简直是“如果”与“万一”的终极系统化。

      我先用一句话概括,然后再分拆:

      模态逻辑 = 把“可能”、“必要”等语气词,变成有规则的、可以计算的逻辑结构; 可能世界语义学 = 为这些语气词搭建一个想象中的“宇宙地图”。


      🌌 一、模态逻辑是啥?

      普通逻辑只讲真假:

      命题 P 是真还是假。

      模态逻辑加上语气修饰符(模态词 modal operators):

      | 模态词 | 逻辑符号 | 意义 | | --------------- | ---- | -------------- | | 必然(necessarily) | □P | 在所有可能情况下,P 都为真 | | 可能(possibly) | ◇P | 在某些可能情况下,P 为真 |

      比如:

      • “太阳明天升起” → 你可以说:它是可能的(◇P);
      • “2+2=4” → 你说:它是必然的(□P);

      模态逻辑让这些说法不再只是语言习惯,而是逻辑公式


      🧭 二、那什么是“可能世界语义学”?

      你可能会问:

      “那‘所有可能情况’是哪来的?我们凭啥说清楚‘必要’或‘可能’?”

      这就引入了哲学史上最有想象力的发明之一:

      ✅ 可能世界语义学(Possible Worlds Semantics)

      它认为:每一种可能的情况,都可以被想象成一个“可能世界”。

      就像是一堆平行宇宙:

      • 世界A:你在看这段话;
      • 世界B:你没点开这段话;
      • 世界C:你其实是只狗,但喜欢哲学。

      在这个设定中:

      • □P 表示:在所有可能世界中,P 都为真;
      • ◇P 表示:在至少一个可能世界中,P 为真。

      这种理论体系由**克里普克(Saul Kripke)**在1960年代构建,成为现代模态逻辑的核心。


      🔄 三、怎么“用可能世界推理”?

      克里普克构建了一种叫Kripke模型的结构:

      • 有一组可能世界 W;
      • 有一个“可达关系” R(哪些世界互相可见);
      • 在每个世界 w,有一个真值赋值函数 v;

      于是我们可以精确判断:在某个世界里,P 是否必要可能为真。


      🤹 四、举个有趣例子

      假设:

      • 世界A:你是中国人;
      • 世界B:你小时候去了英国,成了英国人;
      • 世界C:你没出生。

      我们说:

      • “你可能成了英国人” → ◇(你是英国人) → 成立,因为在 B 为真;
      • “你必然是中国人” → □(你是中国人) → ❌ 不成立,因为 B 世界反了。

      这时我们看清楚了:“你现在是中国人”是真,但“你必然是中国人”是假的。

      模态逻辑就是这么细,甚至可以用来分析时间、知识、信仰、道德义务……


      🧠 应用场景

      | 场景 | 领域 | 怎么用 | | ----- | -------------- | --------------------- | | 哲学 | 形而上学、语言哲学、伦理学 | 解释“可能”、“必须”、“应该”的真理状态 | | 计算机科学 | 程序验证、AI规划、时态逻辑 | 判断系统状态变化与路径是否合法 | | 语言学 | 语义学、语用学 | 分析语气动词、假设语句含义 | | 法律 | 权利与义务的条件结构 | 比如“你应当归还财产”属于规范模态 |


      ✨ 总结金句(可用作视频结尾或哲学文案)

      “模态逻辑不是让我们思考现在是什么,而是追问——世界可以是什么。”

      或:

      “可能世界语义学,把‘如果’变成了地图,把‘应该’变成了路径。”


      要不要我给你写一个短视频剧本?比如《你有多少个你:可能世界语义学通俗炸裂版》🎬🧠

    1. 批判“给定之神话”

      你要深挖“给定之神话”(Myth of the Given)这块,就等于直接拿起了麦克道尔《心灵与世界》里最锋利的一把刀。我们来一刀一刀剖开——看他是怎么砍断现代认识论的“神话依赖”,然后缝合起“经验 × 理性 × 世界”的三角关系的。


      🧙‍♂️ 什么是“给定之神话”?

      简单说,就是一种**“经验是纯粹、前概念的感官基础”的信仰**。它相信:

      “你先有一堆未经加工的‘感官数据’,这些是由世界直接‘给你’的,然后你再用理性去理解它们、加工它们、推理它们。”

      这就像你打开了快递盒子,里面装满了“生数据”,你再慢慢加工出“知识”。


      🧠 麦克道尔说:这套是个“神话”。

      为啥?因为它幻想经验是独立于概念运作的“感官输入”,但:

      你能意识到“这是感官输入”,本身就说明你已经在“概念空间”里了。

      你不是先接收“感官块”再加工出“树”, 而是你一开始就以“看到树”的方式经验这个世界。


      🎯 用人话说:

      “给定论”逻辑如下:

      1. 世界 →
      2. 感官输入(给定的经验) →
      3. 理性加工 →
      4. 知识、判断、理解

      麦克道尔说:❌ 这中间2和3是分不开的。 感官输入根本不是“纯粹输入”,它已经被你以某种理解方式体验了


      🌰 举个经典栗子:

      你走进一个房间,看见一个棕色的椅子。

      “给定之神话”说:

      “你看到的是:光线、形状、颜色——然后你推理出:啊,是一把椅子。”

      麦克道尔说:

      ❌“错!你不是看到形状再推断出椅子——你就是‘以椅子的方式’在经验那个东西。” ✅经验本身已经是概念性渗透的。


      🧱 为什么这很重要?

      因为如果你真的相信“经验是前概念的”,你就会陷入两个大坑:

      1. 无法解释经验为何能支持知识: → “纯感官数据”无法说明它跟知识判断有什么关系,它像声音背景噪音一样,根本无法“说话”。

      2. 无法说明经验的可错性: → 如果经验是“给定”的,那它就无法出错,但我们明明会看错、听错、误认东西。

      所以,麦克道尔说:“经验如果不能参与理由结构(space of reasons),就无法成为知识基础。”


      🧘‍♂️ 深层逻辑一览:

      | 给定之神话 | 麦克道尔反对的关键 | | ----------- | ------------- | | 感觉是“原始事实” | 感觉也要能进入“理由空间” | | 经验是非概念的“给定” | 经验=概念性地被给予 | | 理性=加工器 | 理性=经验的结构本身 | | 知识=从感觉中推出 | 知识=在概念中理解世界 |


      🎬 比喻总结(哲学短片设定)

      🎥 设想一个快递比喻:

      • 传统给定论:你收到快递(感官数据),再拆封加工(理性判断) → 知识产品
      • 麦克道尔式经验:快递早就按你的理解模式打包好了,你打开的瞬间就知道“这是椅子”

      你以为你在“拆开世界”,其实你在“以理解方式接触世界”。


      ✒️ 结语金句(麦克道尔式):

      “给定之神话就是:以为我们能在概念之外抓住世界; 但真正的经验,是我们在世界中活出概念的方式。


      如果你愿意,我可以给你写一期哲学短视频脚本叫:

      📦《世界不是送你数据包,是送你“能被理解的现实”——麦克道尔暴打给定论》

      场景可以是哲学家们在收快递,别人都拆“数据包”,只有麦克道尔拿着概念标签对着世界说:“它早就写好了”。要整一发吗?😎

    1. NOTE DE SYNTHÈSE

      Sujet : La production sociale des inégalités de santé : Le cas de la vaccination et de la crise COVID-19

      Source : Extraits de "La production sociale des inégalités de santé (4) - Nathalie Bajos (2024-2025)" - Intervention de Jérémy Vart

      Date : 2024-2025 (selon la source)

      Introduction :

      • L'intervention de Jérémy Vart, sociologue et chercheur à l'INSERM, s'inscrit dans une séance dédiée à la production sociale des inégalités de santé, en se focalisant spécifiquement sur les enjeux de vaccination, notamment dans le contexte de la crise COVID-19.

      S'appuyant sur l'intensification récente des travaux en sciences sociales sur les rapports aux vaccins, l'analyse vise à contextualiser les observations faites pendant l'épidémie de COVID par rapport à d'autres vaccins et aux données antérieures à la crise.

      L'exposé s'articule autour de trois paradoxes majeurs qui émergent de l'étude des "rapports ordinaires au vaccin", c'est-à-dire les processus de réflexion et de décision des usagers.

      Thèmes Principaux et Idées Clés :

      • L'évolution de la recherche en sciences sociales sur la vaccination :
      • Il y a eu un regain d'intérêt pour les maladies infectieuses et la vaccination dans les sciences sociales depuis la grippe AH1N1 en 2009-2010.
      • La période COVID-19 a vu une intensification sans précédent de ces travaux, comme en témoigne l'augmentation significative du nombre de publications annuelles sur le sujet dans des bases de données comme PubMed.
      • Ce développement a permis d'obtenir des analyses beaucoup plus fines et riches des inégalités sociales face à la vaccination.
      • Cependant, malgré les progrès, de nombreuses questions nouvelles et sans réponses claires subsistent, soulevées par la combinaison de ces analyses et des transformations majeures du monde de la vaccination.
      • Citation clé : "...on a vu euh un regain d'intérêt pour les maladies infectieuses et la et la vaccination et on a notamment vu une multiplication des travaux de de de sciences social sur les rapports ordinaires au vaccin euh et qui s'est encore plus intensifié pendant la période de de la COVID-19..."

      Distinction Attitude/Comportement en matière de vaccination :

      • Une distinction cruciale, bien que potentiellement simpliste, est faite entre ce que les gens font (comportement, souvent mesuré par la couverture vaccinale) et ce que les gens pensent (attitude, incluant les réflexions, doutes, changements d'avis).
      • Cette distinction est fondamentale car elle met en évidence une disjonction fréquente : de nombreuses personnes se font vacciner malgré des doutes persistants, souvent sous l'effet de pressions sociales, notamment les dispositifs de contrainte et d'obligation (comme le pass sanitaire pendant le COVID-19).
      • Inversement, des personnes favorables à la vaccination peuvent ne pas se faire vacciner en raison d'obstacles (matériels, temporels) ou d'un simple oubli lorsque l'intention n'est pas très forte.

      • Citation clé : "...de nombreuses nombreuses personnes se font vacciner malgré la persistance de doute fort malgré le fait qu'ils n'ont pas été convaincus de l'utilité de tel ou tel vaccin on l'a notamment vu pendant l'épidémie de COVID-19 après la mise en place du du pass sanitaire..."

      Gradient Social des Comportements Vaccinaux (Couverture Vaccinale) : * Le constat d'un gradient social de la vaccination contre le COVID-19 (les personnes en bas de l'échelle sociale étant moins vaccinées) est largement confirmé par de nombreuses études utilisant diverses données (enquêtes par questionnaire, analyses de couverture vaccinale). * Ce gradient n'est pas spécifique au COVID-19 ni à la période récente ; il existe sur d'autres vaccins (comme ROR, grippe) et était déjà observable avant l'épidémie de COVID, bien que les données COVID soient peut-être les meilleures pour étudier ces inégalités. * Ce gradient est également observé dans la plupart des pays qui publient des données sur le sujet, les plus diplômés et les plus aisés étant généralement davantage vaccinés. * Citation clé : "...cette sous-vaccination des publics en bas de l'échelle sociale elle est pas restreinte à la vaccination contre contre le Covid ... On la retrouve sur d'autres vaccins au cours de cette période du Covid..." * Mécanismes Expliquant le Gradient Social des Comportements : * Se faire vacciner nécessite de mobiliser diverses ressources : * Ressources matérielles : coût (même si le vaccin COVID était gratuit, d'autres ne le sont qu'à 70% par la sécurité sociale, laissant la question de l'avance des frais et des complémentaires santé), transport, mais surtout le temps et la disponibilité mentale. Le circuit de vaccination en France, notamment en médecine libérale (prescription, récupération, injection), repose une charge importante sur la personne. * Ressources culturelles : maîtrise des outils d'information, de la langue, connaissance du système de santé. La maîtrise de plateformes en ligne comme Doctolib a favorisé l'accès des plus aisés. * L'offre vaccinale : La manière dont le système de santé prend en compte (ou non) ces différences d'accès est cruciale. Les facteurs favorisant de fortes couvertures vaccinales observés dans d'autres pays incluent : * L'organisation du système de soins autour de centres de santé locaux (guichet unique, association de la vaccination à d'autres prises en charge). * Le développement d'actions ciblées pour les publics éloignés du système de santé (partenariats communautaires, adaptation de la communication, y compris linguistique). * Paradoxe 1 : L'efficacité de la routine institutionnelle (la dissolution de la décision individuelle) : * L'efficacité de la vaccination en centres de santé (comme les PMI en France, fréquentées par des publics plus défavorisés mais dont les enfants sont mieux vaccinés) suggère que la réduction des inégalités passe moins par l'augmentation des ressources des individus pour en faire des "citoyens sanitaires éclairés" que par la simplification et la routinisation de l'acte vaccinal. * Une politique vaccinale est d'autant plus efficace que l'usager a le moins besoin de s'investir. La vaccination par défaut, intégrée à une prise en charge globale et ne nécessitant pas un investissement cognitif important, minimise le rôle de la décision individuelle. * Des études anciennes (comme celles de Marenko et Govedarik sur les PMI de Rennes dans les années 70) ont montré que des publics très défavorisés, peu informés sur les vaccins, avaient leurs enfants très bien vaccinés car l'acte était rendu "évident, voire invisible" au sein d'une prise en charge de confiance et régulière. * Citation clé : "...le succès de la vaccination en centre de santé nous rappelle aussi qu'une politique vaccinale elle est d'autant plus efficace que l'usager a le moins besoin de s'investir dans celle-ci la politique vaccinale elle est jamais aussi efficace que lorsqu'elle est routinisée et que l'usager n'a que peu de décisions à prendre..." * Gradient Social des Attitudes Vaccinales : * Un gradient social des attitudes (défiance, hésitation) à l'égard de la vaccination COVID est également observé dans de nombreuses enquêtes. Ce gradient est fortement lié aux "mauvaises expériences et au manque de confiance à l'égard des acteurs investis dans les politiques vaccinales", comme l'a souligné Nathalie Bajos. * Cependant, ce gradient social des attitudes n'est pas toujours retrouvé sur d'autres vaccins ou dans d'autres pays. Les Baromètres Santé de Santé publique France montrent que les différences d'attitude selon le diplôme et le revenu étaient faibles, voire inexistantes, avant 2009, se renforçant après, et surtout à partir de 2017-2018 et pendant le COVID-19. * Paradoxe 2 : L'acceptation malgré la défiance institutionnelle : * Ce paradoxe réside dans le fait qu'une large part des personnes ne faisant pas confiance aux décideurs politiques et aux autorités de santé "épargnent les vaccins de leur regard critique" ou, du moins, ont une confiance suffisante pour certains vaccins. * Les données d'enquête montrent que même parmi les personnes déclarant ne pas avoir du tout confiance dans les agences de santé, une minorité seulement est défavorable aux vaccins en général, et encore moins à des vaccins spécifiques comme le ROR. * Ce paradoxe renvoie aux analyses de Beck et Giddens sur la confiance dans la modernité : face à la complexité des risques, l'enjeu est de savoir sur quels sujets être vigilant, car il est impossible de se méfier de tout. Les mobilisations, débats publics et l'actualité médiatique jouent un rôle crucial en signalant les sujets "problématiques". * L'émergence de controverses publiques visibles sur les vaccins en France est relativement récente (fin des années 90 pour l'hépatite B, intensification depuis H1N1 en 2009) et semble être un élément essentiel pour que les inégalités sociales se reflètent dans les perceptions vaccinales. * Citation clé : "...une grande partie des personnes qui ne font pas confiance aux décideurs politiques euh et aux autorités de santé épargne les vaccins de leur de leur regardard critique de leurs doutes de leur méfiance..." * La politisation de la vaccination : * Dans les années précédant la crise et pendant celle-ci, les personnalités politiques ont de plus en plus pris part aux débats sur la vaccination, intégrant la question dans la compétition partisane. * Cela se reflète dans les attitudes du public : depuis environ 2018, un gradient politique des rapports aux vaccins est observé. Pendant le COVID-19, les personnes se sentant proches des partis d'extrême gauche ou d'extrême droite, ainsi que celles ne se sentant proches d'aucun parti, ont montré des intentions de vaccination et des taux de vaccination inférieurs à ceux proches du centre (qui montrent une "sur-vaccination"). * Ces différences persistent même en contrôlant d'autres facteurs socio-démographiques (âge, éducation, revenu). La confiance institutionnelle et le degré d'engagement politique sont des facteurs très importants d'hésitation. * Cette politisation redouble les logiques d'inégalité en recoupant les inégalités de santé avec des inégalités politiques. * Le rôle des pratiques informationnelles et le "manque de culture scientifique" : * L'idée courante selon laquelle les doutes s'expliquent par le manque de culture scientifique (un "gradient de compétences culturelles/cognitives") est examinée. * Le diplôme est associé à plus de vaccination et d'attitudes favorables. Des indicateurs de littératie en santé ou scientifique sont également associés à moins d'hésitation vaccinale dans certaines études. * Cependant, ce lien est à tempérer : * Ces variables perdent beaucoup de leur pouvoir explicatif lorsqu'on intègre la confiance dans l'analyse. Les différences d'éducation cachent en partie des différences de niveau d'engagement politique et de confiance institutionnelle. * Le diplôme n'est pas un "bouclier parfait" : l'hésitation vaccinale est répandue, même parmi les plus diplômés (une part significative des Bac+3 et Bac+5 avaient des doutes ou n'avaient pas l'intention de se faire vacciner contre le COVID-19 à certains moments). * Paradoxe 3 : Les ressources culturelles peuvent favoriser la susceptibilité aux discours critiques : * Les femmes ont tendance à être plus hésitantes que les hommes en matière de vaccination. Ceci n'est pas lié à un manque de compétences, mais potentiellement à leur "plus grande propension à s'investir sur les questions de santé", à s'y intéresser, à s'informer auprès de diverses sources. * Ces dispositions, qui devraient en principe favoriser une attitude favorable, peuvent jouer en sens inverse en les rendant plus susceptibles de croiser des discours critiques sur les vaccins et d'y voir un écho (références à des scandales passés, inégalités sociales de santé, etc.). * Il existe des formes "très compétentes" d'hésitation vaccinale. Une logique d'investissement dans la santé ("healthism" ou "santéisme"), combinée à une confiance limitée dans les acteurs de santé publique, peut produire autant de réticence que l'absence d'investissement. * La "désinformation" ne se réduit pas à une distinction claire entre vrai et faux. Les critiques des vaccins imitent souvent les modes de communication scientifique, rendant la frontière floue pour le public. Le choix de croire l'un ou l'autre repose finalement sur la confiance accordée aux institutions et aux types de sources d'information consultées. * Citation clé : "...dans certains cas c'est au contraire le fait même de disposer des ressources euh qui euh favorisent la susceptibilité au discours critique des vaccins..." * Conclusion : Nécessité d'articuler inégalités sociales, pratiques culturelles et transformations médiatiques : * La littérature sur la désinformation s'est trop focalisée sur les connaissances et capacités cognitives, ce qui a conduit à une "dissolution de la thématique des inégalités sociales". * Comprendre la désinformation et le rôle des réseaux sociaux nécessite de replacer ces dimensions dans un cadre d'analyse plus large qui articule les inégalités sociales, les pratiques culturelles (socialement situées, liées aux socialisations de classe, genre, race), et une analyse fine de la transformation des espaces médiatiques (y compris l'émergence de médias mainstream d'extrême droite diffusant de fausses informations). * Ne pas adopter cette perspective risque de retomber sur des "tropes qui assignent le public à l'irrationalité", ce qui renforce le fossé perçu entre décideurs et public et contribue davantage au problème qu'à sa solution.

      Points Importants à Retenir :

      • Les inégalités sociales dans la vaccination sont un phénomène bien établi en France et ailleurs, non spécifique au COVID-19.
      • La disjonction entre attitudes et comportements est importante : le comportement vaccinal est influencé non seulement par les croyances mais aussi par les pressions sociales et les obstacles d'accès.
      • L'efficacité de la vaccination peut résider moins dans la facilitation de la décision individuelle éclairée que dans la routinisation et l'intégration de l'acte dans une prise en charge globale simplifiée.
      • Le gradient social des attitudes vaccinales en France est un phénomène relativement récent, lié à l'émergence de controverses publiques et à la politisation du sujet.
      • La défiance institutionnelle n'implique pas nécessairement une défiance envers tous les vaccins ; les mécanismes de confiance sélective et l'influence des débats publics sont cruciaux.
      • Les ressources culturelles et l'engagement sur les questions de santé peuvent, paradoxalement, augmenter la sensibilité aux discours critiques sur les vaccins.
      • Une compréhension adéquate des rapports à la vaccination et de la "désinformation" nécessite d'intégrer les dimensions d'inégalités sociales, de pratiques culturelles et de transformation des espaces médiatiques, au-delà d'une simple focalisation sur les connaissances ou les capacités cognitives individuelles.

      Implications pour la Prévention et les Politiques Publiques :

      • Les politiques vaccinales devraient davantage cibler la simplification de l'accès et la routinisation de l'acte, en s'inspirant potentiellement du modèle des centres de santé locaux.
      • La communication doit être adaptée aux divers publics, en tenant compte des barrières linguistiques et culturelles, ainsi qu'en s'appuyant sur des acteurs communautaires de confiance.
      • Il est crucial de comprendre les mécanismes complexes par lesquels la défiance et les controverses s'articulent avec les inégalités sociales et les pratiques informationnelles pour mieux y répondre.
      • Éviter les discours qui essentialisent la "désinformation" et stigmatisent le public en termes d'irrationalité ou de manque de savoir.
      • Cette note de synthèse vise à capturer l'essence de l'intervention de Jérémy Vart, en soulignant les principaux arguments et les paradoxes qu'il met en évidence pour enrichir la compréhension des rapports sociaux à la vaccination.
    1. Résumé de la vidéo [00:00:00][^1^][1] - [00:29:01][^2^][2]:

      Cette vidéo présente une conférence de Pierre-Michel Menger sur l'éducation et l'évaluation des performances, avec un accent particulier sur l'orientation scolaire et les inégalités sociales qui en découlent.

      Pascal Bressoux, professeur à l'Université Grenoble Alpes, discute des facteurs individuels, institutionnels et contextuels qui influencent les parcours scolaires des élèves, notamment les choix d'orientation et leur relation avec le statut socio-économique.

      Points saillants: + [00:02:31][^3^][3] Les choix d'orientation * Influencés par les aspirations familiales et les schémas établis * Différences notables selon la catégorie sociale et le sexe des élèves * Phénomène d'autosélection où certains groupes sociaux limitent leurs ambitions + [00:07:04][^4^][4] Facteurs déterminant l'orientation * Travaux de recherche soulignant l'importance des aspirations personnelles * Influence des coûts, des risques et des bénéfices perçus dans la poursuite des études * Sous-estimation de la valeur scolaire personnelle affectant les choix d'orientation + [00:14:07][^5^][5] Étude empirique sur l'orientation en fin de 3e * Analyse des déterminants de l'orientation après le collège * Impact des recommandations du collège sur les vœux d'orientation des familles * Rôle des notes de contrôle continu et de l'indice social dans les décisions d'orientation + [00:20:11][^6^][6] Influence des notes et de l'origine sociale * Les notes en art et technologie ont un effet inverse sur les intentions d'orientation * Les enfants de catégories sociales élevées ont plus de chances de choisir une seconde générale * Les recommandations des collèges tentent de compenser les tendances d'autosélection

      Résumé de la vidéo [00:29:03][^1^][1] - [00:36:31][^2^][2]:

      Cette partie de la vidéo aborde l'éducation et l'évaluation des performances en France, en se concentrant sur l'impact de l'origine sociale sur les recommandations scolaires et les choix d'orientation des élèves.

      L'orateur, Pierre-Michel Menger, examine comment les indices sociaux influencent positivement les recommandations et les vœux des élèves, même à notes et intentions identiques, renforçant ainsi les inégalités sociales.

      Points forts: + [00:29:03][^3^][3] Influence de l'origine sociale * À notes identiques, les recommandations favorisent les élèves de milieux sociaux élevés * Les élèves de catégories favorisées reçoivent plus de recommandations pour la seconde GT * L'institution accentue les biais sociaux existants + [00:31:19][^4^][4] Impact sur les vœux d'orientation * Les vœux sont également influencés par l'origine sociale après les recommandations * Les élèves de milieux favorisés ont tendance à établir des vœux plus ambitieux * Les différences sociales s'accroissent tout au long du processus d'orientation + [00:32:58][^5^][5] Effets contextuels des collèges * Les politiques de notation des collèges affectent les intentions et les vœux des élèves * L'effet "Big Fish Little Pond" influence la perception de soi et les aspirations futures * La composition sociale des collèges a un effet de contagion sur les aspirations des élèves

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    1. NOTE D'INFORMATION

      Objet : Analyse des enjeux et des défis de l'orientation au collège et au lycée en France, selon un rapport de la Cour des comptes et les réponses du Ministère de l'Éducation nationale et de l'Association Régions de France.

      Date : 19 mars 2025

      Sources :

      Excerpts from "https://www.ccomptes.fr/sites/default/files/2025-03/20250319-RPA2025-volume1-orientation-college-lycee.pdf"

      1. Introduction : L'orientation au cœur du système éducatif – Enjeux et Contexte

      L'orientation des élèves au collège et au lycée est un processus essentiel qui les guide à travers leur parcours scolaire et vers l'insertion professionnelle.

      Ce processus est décrit comme un "cheminement qui court sur plusieurs années".

      Les moyens publics consacrés à cette politique sont estimés à environ 400 M€ et 8 000 équivalents temps-plein.

      Les enjeux de l'orientation sont considérables, tant au niveau individuel que collectif. Ils visent à garantir l'équité, en dépassant les déterminismes sociaux, de genre et territoriaux, et à répondre aux besoins en compétences du marché de l'emploi et de la société.

      La loi du 5 septembre 2018 a établi une compétence partagée sur l'information à l'orientation entre les régions académiques et les régions, entraînant une réorganisation de l'Onisep.

      Cependant, la loi "ne permet pas d’aboutir à une situation claire". Une "multitude d’acteurs, publics et privés, ont émergé et jouent un rôle croissant".

      Les jeunes et leurs parents se sentent souvent "en manque de repères face à une offre de formation foisonnante, aux règles du jeu opaques et instables".

      Un sondage de mai 2024 par la Cour indique que 35 % des collégiens et 25 % des lycéens se disent insatisfaits des informations et conseils reçus. De plus, près de 20 % des bacheliers qui poursuivent leurs études regrettent leur choix d'inscription.

      2. Déterminismes et Inégalités dans l'Orientation

      Le processus d'orientation est fortement influencé par les résultats scolaires, l'image sociale des filières et l'offre de formation.

      Déterminismes sociaux et territoriaux : L'orientation "tend donc plutôt à amplifier le déterminisme social". Après la classe de troisième, près d'un tiers des élèves (32% en 2022) rejoignent la voie professionnelle.

      Les élèves issus de milieux peu favorisés sont davantage représentés dans les lycées professionnels.

      "À notes équivalentes, les familles de milieux défavorisés font beaucoup moins souvent des choix d’orientation vers la seconde générale et technologique" et les décisions des équipes éducatives peuvent être influencées par le contexte social de l'élève.

      Le lieu de résidence joue également un rôle, notamment pour les élèves en zone rurale éloignée où la voie professionnelle est plus souvent choisie en raison de difficultés de mobilité et d'un attachement au marché du travail local.

      Le dispositif des Cordées de la réussite, bien que non évalué de manière exhaustive, semble avoir un impact positif sur le taux de proposition d'admission dans Parcoursup pour les élèves participants.

      Déterminismes de genre : Les choix d'orientation "restent très genrés à tous les niveaux de formation". Les parents jouent un rôle majeur dans cette reproduction sociale.

      Malgré des actions visant à sensibiliser et à lutter contre les stéréotypes, la mixité nécessite "une action concertée et continue de l’enseignement supérieur et du monde du travail dans les secteurs traditionnellement très genrés".

      3. La Valorisation des Enseignements Professionnels et Technologiques

      Un objectif prioritaire du gouvernement est de "Refonder l’orientation des élèves", en mesurant le nombre de métiers connus en fin de troisième et le taux d'élèves ayant bénéficié de la découverte des métiers.

      La découverte des métiers est généralisée "dans toute la mesure du possible" dans tous les collèges depuis la rentrée 2023.

      La part des élèves en voie professionnelle a diminué globalement (de 38% en 2007 à 32% en 2022), mais les demandes des familles pour cette voie ont augmenté récemment (de 32,5% en 2020 à 36,2% en 2024), témoignant d'une "réels progrès dans la valorisation de la voie professionnelle".

      Cependant, le secteur industriel souffre encore d'un "déficit d’image".

      La coexistence des voies professionnelle et technologique, avec une "image de relégation attachée à la voie professionnelle auprès des familles et des enseignants", contribue à ce sentiment.

      Un rapprochement entre ces voies est suggéré, comme le modèle suisse où la filière professionnelle est "fortement valorisée" et suivie par 70 % des élèves, incluant les enfants de cadres.

      4. L'Accompagnement à l'Orientation : Un Besoin Insatisfait

      Il existe un "important besoin d’accompagnement à l’orientation insatisfait" qui a conduit à l'émergence d'une "multitude d’intervenants".

      Les lycéens s'informent principalement via les forums/salons de l'étudiant (41%), les journées portes ouvertes/immersions dans les établissements d'enseignement supérieur (38%) et le site de l'Onisep (36%).

      Le marché privé du conseil en orientation se développe en réponse à ce besoin, "accroissant en retour les inégalités entre les jeunes".

      5. L'Organisation et les Moyens de l'Orientation dans les Établissements Scolaires

      Le corps des psychologues de l'éducation nationale (psyEN), remplaçant les conseillers d'orientation-psychologues, s'est recentré sur le suivi psychologique des élèves.

      Le ratio d'élèves par psyEN est de 1 147 élèves par psychologue de l’Éducation nationale, ne permettant pas une action individualisée.

      Le transfert des missions des psyEN vers les régions est jugé "peu praticable, à l’heure actuelle".

      La mission d'éducation à l'orientation, confiée aux enseignants, est "insuffisamment accompagnée".

      Bien que l'orientation fasse partie de leur référentiel de compétences, les maquettes de formation initiale ne comportent pas de "formation obligatoire sur ce sujet".

      Les heures d'accompagnement à l'orientation prévues au collège et au lycée général et technologique ne sont pas des "moyens fléchés" et sont perçues comme "non financées et non obligatoires".

      La Cour estime le besoin de financement complémentaire pour sécuriser ces heures à entre 134 M€ et 309 M€ selon les modalités.

      Deux outils sont en développement pour appuyer les enseignants : le programme Avenir(s) de l'Onisep (doté de 20 M€ sur 10 ans) qui vise à structurer l'outillage pédagogique et à créer un portfolio pour les élèves, et le module MonProjetSup (développé par le ministère de l'enseignement supérieur en lien avec l'Onisep) pour aider les lycéens à préparer leurs vœux dans Parcoursup.

      L'absence de transparence des critères de décision dans Parcoursup est soulignée comme une difficulté.

      6. La Répartition des Compétences entre l'État et les Régions

      La répartition actuelle des compétences entre l'État et les régions "prête à confusion".

      Les régions ont la responsabilité de la coordination et de l'animation de l'orientation tout au long de la vie pour les adultes, mais leur compétence pour les publics scolaires, étudiants et apprentis se limite à "l'information sur les métiers et les formations".

      La phrase de la loi "la région organise des actions d’information", et non "les actions d’information", est jugée limitée.

      Les régions revendiquent un "transfert plein et entier de la compétence « orientation »", mais contestent l'analyse de la Cour selon laquelle cela impliquerait de leur confier les décisions d'orientation et d'affectation.

      Elles estiment que ces décisions relèvent de l'Éducation nationale.

      La profusion de sites d'information et d'orientation (avec des exemples de sites publics et privés) illustre cette complexité.

      Le développement de la plateforme Avenir(s) par l'Onisep est perçu par les régions comme faisant "doublon avec la compétence régionale sur l’information métiers" et rendant "invisibles les sites que toutes les régions ont développés".

      Les régions demandent une clarification en remplaçant "des actions" par "les actions" dans le code du travail et un transfert global des missions et moyens nécessaires.

      L'enveloppe actuelle de 8 M€ transférée aux régions pour l'information territorialisée est jugée "très insuffisante" au regard de leur engagement réel (plus de 170 M€ en 2024).

      La mise en synergie des nombreuses structures accueillant les jeunes (CIO, bureaux Information Jeunesse, missions locales, structures régionales, chambres consulaires) est nécessaire pour améliorer l'efficience et la lisibilité pour le public.

      Le "bassin d’éducation et de formation apparaît comme le niveau pertinent pour que les acteurs se connaissent et travaillent de manière harmonisée".

      7. La Transformation de l'Offre de Formation Professionnelle

      L'offre de formation "détermine pour une large part l’orientation des jeunes".

      Les taux d'emploi à six mois des diplômés du baccalauréat professionnel (48%) et du CAP (33%) sont relativement bas (mais plus élevés que pour les bacheliers généraux ou technologiques n'ayant pas poursuivi d'études supérieures).

      L'application Inserjeunes vise à fournir des informations sur les taux de poursuite d'études et d'insertion.

      La "transformation indispensable de l'offre de formation professionnelle" est une priorité pour une meilleure insertion des jeunes en lien avec les besoins des territoires.

      L'affectation dépend des capacités disponibles, et 25% à 30% des élèves n’obtiennent pas leur premier vœu, ce qui "peut renforcer le sentiment d’orientation subie".

      La baisse prévue des effectifs de lycéens à partir de 2028 offre une "opportunité de conduire cette transformation".

      Les campus des métiers et des qualifications sont un exemple d'articulation entre offre de formation et orientation, mais leur impact est variable.

      8. Conclusions et Recommandations de la Cour des Comptes

      Malgré les efforts, l'orientation reste marquée par de forts déterminismes sociaux, territoriaux et de genre.

      L'éducation à l'orientation au collège est difficile à mettre en place en raison du manque de formation des enseignants et de l'absence de moyens fléchés pour les heures dédiées.

      La répartition des compétences entre l'État et les régions doit être clarifiée, et une meilleure articulation locale des acteurs est nécessaire.

      L'orientation est indissociable de l'offre de formation professionnelle, qui doit s'adapter aux besoins locaux.

      La Cour formule les recommandations suivantes :

      • Insérer dans les maquettes de formation initiale des enseignants un module obligatoire sur la compétence orientation.
      • Adapter l'emploi du temps des professeurs principaux ou référents pour leur permettre d'assurer leur mission d'orientation.
      • Expérimenter avec une ou plusieurs régions volontaires un rapprochement entre les voies du lycée, professionnelle, technologique et générale.

      9. Réponses et Perspectives

      Le Ministère de l'Éducation nationale signale qu'une concertation nationale sur l'orientation est en cours (novembre 2024 - mars 2025) pour "faire de la politique d’orientation un levier de réussite et d’égalité des chances".

      Il souligne l'importance du programme Avenir(s) pour créer un "service public national, gratuit, exhaustif et égalitaire de l’orientation".

      Concernant la recommandation 1, le ministère indique que la compétence d'orientation est déjà incluse dans le référentiel de formation des enseignants et que la réforme de la formation initiale permettra de réfléchir à l'évolution des contenus.

      Il souligne également l'effort en matière de formation continue sur l'orientation (50 294 journées en 2023-2024).

      Concernant la recommandation 2, le ministère ne prévoit pas de quantifier le volume horaire de la mission d'orientation pour éviter la rigidité et ne pas nuire à la mission de coordination.

      Il précise que le dispositif actuel permet l'intervention de divers personnels et que tous les professeurs ont un rôle en matière d'orientation.

      Concernant la recommandation 3, le ministère y voit un intérêt pour une perspective décloisonnée et travaillera en articulation avec l'enseignement supérieur.

      Le ministère mentionne également une expérimentation d'"option santé" dans les lycées de déserts médicaux pour lutter contre les déterminismes territoriaux.

      Il précise que MonProjetSup est intégré à Avenir(s) et vise à fournir des suggestions personnalisées basées sur les données de Parcoursup.

      Il rappelle le rôle des psyEN en matière d'orientation, malgré une charge de travail accrue sur d'autres missions.

      Régions de France partage le constat de la confusion des compétences et le manque de repères pour les jeunes et les parents.

      Elles souscrivent aux objectifs de lutte contre les déterminismes et de valorisation des métiers.

      Elles partagent aussi le constat de l'émergence des acteurs privés.

      Cependant, elles contestent l'idée que leur demande de compétence pleine et entière implique de prendre les décisions d'orientation et d'affectation, qui relèvent selon elles de l'Éducation nationale.

      Elles demandent une clarification législative en remplaçant "des actions" par "les actions" dans le code du travail.

      Elles voient la plateforme Avenir(s) comme un doublon.

      Elles réclament un transfert global des missions et moyens nécessaires, incluant les équipes des directions territoriales ONISEP et les directeurs de CIO, et jugent l'enveloppe actuelle transférée pour l'information "très insuffisante".

      Elles soulignent que les moyens dédiés aux CIO diminuent et que les psyEN se concentrent davantage sur le suivi psychosocial, déportant l'accompagnement de l'affectation vers les régions sans moyens additionnels.

      Régions de France souhaite que le rapport de la Cour contribue à une clarification de la compétence et regrette l'absence de recommandation sur ce sujet.

      Elles souscrivent à l'expérimentation de rapprochement des voies au lycée et partagent le constat de l'inadéquation entre orientation et besoins réels des territoires.

      En synthèse, les points clés à retenir sont :

      Le système d'orientation actuel est complexe, coûteux, et manque de clarté, entraînant une insatisfaction chez les jeunes et leurs parents.

      L'orientation est fortement marquée par les déterminismes sociaux, de genre et territoriaux, avec un besoin de renforcer l'équité.

      La valorisation de la voie professionnelle est un enjeu majeur, avec un modèle comme la Suisse cité en exemple.

      Le besoin d'accompagnement à l'orientation est important mais insuffisamment satisfait par le système éducatif public, favorisant l'émergence d'acteurs privés et l'accroissement des inégalités.

      La formation des enseignants à l'orientation est jugée insuffisante.

      Les heures dédiées à l'orientation dans les établissements manquent de moyens fléchés et ne sont pas toujours concrétisées.

      La répartition des compétences entre l'État et les régions est source de confusion, et les régions réclament une compétence pleine et entière sur l'information et l'orientation métiers, mais pas sur les décisions d'affectation.

      La profusion d'outils et de structures d'information et d'orientation nécessite une meilleure synergie et lisibilité locale.

      L'offre de formation professionnelle doit être transformée pour mieux s'adapter aux besoins locaux et offrir des parcours d'insertion réussie.

      Des expérimentations, comme le rapprochement des voies au lycée et l'option santé, sont des pistes explorées pour améliorer le système.

      Cette note d'information résume les principaux éléments et les divergences de points de vue entre les acteurs sur la manière d'améliorer l'orientation des jeunes en France.

    1. https://www.youtube.com/watch?v=IWpB1r1B-A0&list=PLX_ensLRxEWDQzzjNvGf2OJPNN3BuNCmv&index=3

      Résumé de la vidéo [00:00:00][^1^][1] - [00:21:12][^2^][2]:

      La vidéo présente une analyse approfondie de la méritocratie, en se concentrant sur les grandes écoles et les classes préparatoires scientifiques en France. Pierre-Michel Menger discute des inégalités d'accès basées sur le genre et l'origine sociale, et explore le fonctionnement interne de ces institutions élitistes.

      Points forts: + [00:00:28][^3^][3] Les grandes écoles et la méritocratie * Examen des concours nationaux comme mécanisme de sélection * Importance historique et universelle des concours + [00:02:16][^4^][4] Avantages et inconvénients des concours * Objectivité et transparence des critères de sélection * Risques liés à la conception des concours et à la chance + [00:03:01][^5^][5] Le rôle de la chance dans la méritocratie * Influence de facteurs aléatoires sur les résultats des concours * Distinction entre mérite et chance dans le succès + [00:06:18][^6^][6] Inégalités dans les classes préparatoires * Accès inégal aux préparations de concours * Hiérarchie et émulation au sein des classes préparatoires + [00:11:09][^7^][7] Classes de niveau et redoublement * Sélection des élèves pour les classes étoilées après la première année * Impact des classes de niveau sur les opportunités et les inégalités + [00:14:27][^8^][8] Classes de niveau et performance éducative * Débat sur l'efficacité des classes de niveau dans l'éducation * Conséquences des classes de niveau sur le classement final des élèves Résumé de la vidéo [00:21:15][^1^][1] - [00:43:18][^2^][2] : La vidéo aborde la méritocratie dans le système éducatif français, en se concentrant sur les classes préparatoires et leur impact sur les inégalités sociales. Pierre-Michel Menger analyse les résultats des concours d'entrée aux grandes écoles et la répartition des élèves selon leur statut socio-économique.

      Points forts : + [00:21:15][^3^][3] Les résultats des concours * Les boursiers sont en moyenne plus en difficulté * Les non-boursiers ont tendance à mieux réussir * Questionnement sur le système de classes préparatoires et son rôle dans la création d'inégalités + [00:22:01][^4^][4] Caractéristiques des élèves * Fort pourcentage d'élèves avec mention très bien au bac * Peu de filles et de boursiers dans les classes préparatoires * Accès aux internats et entraînements supplémentaires + [00:26:04][^5^][5] Répartition en classes étoilées * Les élèves étoilés ont un taux de réussite plus élevé aux concours * Question sur l'effet causal de la répartition en classes étoilées * Impact significatif de l'accès aux classes étoilées sur les résultats aux concours + [00:38:00][^6^][6] Inégalités entre boursiers et non-boursiers * Les boursiers accèdent moins aux classes étoilées * L'écart de réussite aux concours est en partie expliqué par cet accès limité * Importance de considérer l'effet des classes étoilées sur les inégalités sociales Résumé de la vidéo [00:43:20][^1^][1] - [00:49:30][^2^][2]:

      Cette partie de la vidéo discute de la méritocratie dans le contexte des classes préparatoires en France, en se concentrant sur l'institution du redoublement et son impact sur les résultats des concours, en particulier le concours Mines-Ponts. Pierre-Michel Menger analyse les données et révèle des différences de genre dans les taux de redoublement, ainsi que l'attitude des étudiants envers les hiérarchies des écoles d'ingénieurs.

      Points saillants: + [00:43:20][^3^][3] Le redoublement et son impact * Le redoublement a un impact positif sur les résultats en 3e année * Les filles redoublent moins que les garçons * Les non-boursiers redoublent plus que les boursiers + [00:45:30][^4^][4] Les résultats au concours Mines-Ponts * Les résultats varient selon les écoles et les rangs obtenus * Le redoublement peut améliorer significativement les rangs * L'admissibilité est fortement influencée par le redoublement + [00:47:00][^5^][5] Les différences de genre dans la persistance * Les filles montrent moins de persistance dans les environnements compétitifs * Les garçons sont plus sensibles aux hiérarchies des écoles * Les filles sont moins attachées aux hiérarchies entre écoles

    1. So why do some countries have higher GDP per capita than othercountries?

      For a country to grow and sustain a healthy economy, there are five conditions that must be satisfied: 1. Peace and stability - Struggling to survive every day impedes one's ability to work regularly. 2. Quality education - A population that can read, write, and do arithmetic will produce productive workers, savvy customers, innovation, and the spread of technology. 3. Access to capital (money) - Industry requires money which can be accumulated domestically over time or more immediately sourced abroad. 4. Established rule of law - People need to feel confident that their government isn't corrupt and their life, liberty, and property are ensured and protected. 5. Equality and opportunity - By eliminating discrimination against traditionally marginalized groups, people can participate in markets they want and work jobs they are best suited for.

    1. Briefing Document : Journée Jean Zoro 2024 – « Quelle EPS voulons-nous ? » (Présentation du Groupe ÉPIC)

      Date : 2024 Source : Extraits de "C. Albertini, J. Candat & L. Lacoste (ÉPIC) : Journée Jean Zoro 2024 « Quelle EPS voulons-nous ? »"

      Présentateurs : Cyril Albertini, Julien Candat, Lucy Lacoste (Groupe ÉPIC)

      Objet : Présentation de la vision et de la démarche du groupe ÉPIC pour l'éducation physique et sportive (EPS) de demain, en réponse à la thématique de la journée.

      1. Introduction du Groupe ÉPIC

      • Le groupe ÉPIC (Éducation Physique et Innovation Pédagogique et Culturelle) célèbre ses 10 ans d'existence en 2024.
      • Il est composé de 15-16 membres actifs et a publié deux ouvrages et environ 70 articles.
      • La présentation est assurée par trois membres aux profils variés (ancienneté, milieu d'exercice, rôles au sein du groupe) afin de croiser les perspectives.
      • Le groupe se nourrit des échanges avec d'autres groupes et approches en EPS (groupe coopération, groupe analyse de pratique, notamment L. Gosman et N. Terré, groupe plaisir). Ils soulignent l'importance de cette synergie collective au sein de l'EPS.

      2. Constats et Aspirations pour l'École de Demain et l'EPS

      Le groupe ÉPIC identifie trois pistes de réflexion majeures pour l'EPS de demain, découlant de constats sur l'école actuelle :

      Une école bienveillante mais pas toujours exigeante pour tous :

      L'objectif est de "stimuler vraiment les élèves qui sont compétents à l'école afin de porter chacun et chacune à son plus haut niveau de talent et de son mérite". Cela passe par :

      • La différenciation pédagogique.
      • "L'enjeu qui nous échère sur l'évaluation exigeante et bienveillante avec nos [attendus et seuils]".
      • Le suivi des élèves.
      • Nécessité de stabilité et de continuité des programmes : Face à une "valse ministérielle", le groupe souhaite une école "stable et réfléchie sur l'intégralité du parcours". Ils notent positivement la stabilité actuelle des programmes collège (depuis 2015) et lycée (depuis 2017 et 2019). Cependant, ces programmes doivent rester "ouverts" et servir de "guide" et d'"appui", non de "prescription" fermée.
      • Une école respectée : Le manque de respect (entre élèves, envers l'enseignant, au sein de la communauté éducative, et de la part des parents) est une préoccupation majeure. L'EPS doit être un "sanctuaire" et rester "imperméable à certains comportements d'incivilité de la société".

      3. L'Évaluation au Cœur de la Démarche ÉPIC : L'Évaluation Légitime au Service des Apprentissages

      L'évaluation est un concept central pour le groupe. Ils visent une "évaluation légitime et qui doit être au service des apprentissages".

      • Clarté des attendus : Il est crucial de se demander "que peut-on raisonnablement attendre de nos élèves dans notre contexte dans cette classe dans tel [activité] par rapport à un niveau de séquence". Cela nécessite de définir un "dispositif un protocole et des indicateurs".
      • Sortir de l'évaluation sanction : Aller vers une évaluation "lisible, positive et compréhensible et au service des apprentissages".
      • Légitimité de l'évaluation : La légitimité de leur approche d'évaluation repose sur deux points :
      • Des évaluations menées avec des "recherches action de terrain" ("conception continuée dans l'usage").
      • La validation des processus d'évaluation par une "analyse" collective (souhait de collaboration avec le groupe analyse de pratique).
      • Appui sur les textes officiels et les recherches : La démarche s'inscrit dans la continuité des lois de 2013 et 2019 ("évaluer pour faire progresser pour accompagner l'élève"). Ils se réfèrent également aux rapports DEPP, enquêtes et rapports IG qui soulignent l'impact négatif de l'anxiété et du stress sur les apprentissages (effets "toxiques" sur les structures cérébrales comme le cortex préfrontal et l'hippocampe, impacts sur l'estime de soi).

      4. Laisser des Traces Positives et Stimuler la Mobilisation

      L'évaluation doit aussi permettre de "laisser des traces positives aux élèves par également l'évaluation".

      • Traces d'apprentissage : Révéler les "lignes de faille" et les "lignes de force" à travailler, guider vers des tâches simples via le score en situation complexe.
      • Plaisir différé et progression : Le score et les indicateurs permettent à l'élève de "se voir progresser tout au long de la séquence d'enseignement". Ce "retour d'information réguliers" apporte du "sens aux élèves dans les apprentissages".
      • Concordance de sens et mobilisation : En lien avec le groupe Plaisir, la concordance de sens ("ils savent quelles sont leurs lignes de faille qu'il va falloir travailler pour progresser") procure "plaisir et engagement".
      • Pédagogie de la mobilisation : Diminuer les contraintes, tendre vers l'"autodétermination", offrir des "possibilités de choix plutôt que des contraintes à respecter qui sont source du coup d'affect positif et stimulent l'implication des élèves". Lien avec la théorie de l'autodétermination de Deci et Ryan (besoin d'autonomie).
      • Mise en résonance des élèves : S'appuyer sur les travaux de Rosa (qu'est-ce qui "résonne" chez l'élève, le fait retourner vers l'activité physique) et Jaspers (phénoménalité existentielle). Distinguer ce qui "vibre" (plaisir immédiat, expérience mémorable) de ce qui "frotte" (rapport à l'effort, plaisir différé).
      • Effets fertiles : Dépasser les effets toxiques pour aller vers des effets "fertiles positifs" en mobilisant des hormones positives comme l'ocytocine (connaissance de soi, réduction du stress), l'endorphine (plaisir, analgésie), la sérotonine (tolérance à la douleur et aux autres, empathie) et la dopamine (dépassement de soi, motivation).

      5. Les Outils ÉPIC

      Le groupe ÉPIC a développé quatre formes d'outils pour mettre en œuvre sa démarche d'évaluation par indicateur de compétences : "indicants", "visuels", "combinatoires", et "radars".

      • Articulation des dimensions de la compétence : Les outils intègrent les trois dimensions (motricité, méthodologie, social) à travers trois "fils" (rouge pour le moteur, bleu pour le méthodologique, vert pour le social).
      • Hiérarchisation locale et contextualisée des fils : L'importance relative de ces fils varie en fonction du contexte d'enseignement (collège/lycée, public d'élèves, activité, niveau de séquence) et de la "fibre d'enseignant". L'exemple de l'escalade en 6ème est donné où la sécurité (fil bleu méthodologique) est prioritaire, alors qu'en rugby (CA4 collectif), le fil rouge moteur prend une plus grande importance. Cette hiérarchisation doit être "réfléchie et consciente".
      • Progressivité adaptée et individualisée (Fil Rouge Moteur) :Constat de frustration en tant qu'élève (situations trop faciles ou trop difficiles).
      • Passer d'une progressivité "programmée" à une progressivité adaptée aux besoins "révélés par le score".
      • Proposer des situations qui mettent en "réussite dès le départ" pour construire l'estime de soi et la confiance, avant d'introduire des difficultés croissantes.
      • Organisation par "atelier de besoin" où les élèves, guidés par le score en situation complexe, travaillent en autonomie sur des "tâches simples".
      • Exemple de la natation en 5ème avec l'utilisation d'indicateurs combinatoires (temps et coups de bras) pour identifier les problèmes majeurs et orienter vers des situations d'apprentissage spécifiques.
      • Passer d'un "prof magistral descendant" à un "prof satellite" qui accompagne les groupes de besoin.
      • Débat sur la "performance brute" (motricité) versus l'"autoréférencement" (progression individuelle).
      • Articulation avec les "formes de pratique scolaire" et les "objets d'enseignement" définis par le CRÈS.
      • Méthodologie d'indicateurs et outils (Fil Bleu Méthodologique) :Les programmes scolaires et les domaines (notamment le domaine 2) guident le choix des "méthodes" qui deviennent les indicateurs.
      • Développement d'indicateurs 1.0 (plutôt axés motricité et méthodologie) et 2.0 (articulant les trois fils).
      • Création d'outils physiques (ex: scoreur plastifié en badminton) pour accompagner les élèves dans l'observation et l'attribution de points, rendant l'évaluation tangible et favorisant l'engagement et la compréhension des critères.
      • Développement d'outils en partenariat avec Équipe EPS pour une diffusion plus large.
      • Anachronisme des propositions / Paradoxe générationnel : Un jeune enseignant (Julien) développe des outils physiques (tablette physique), tandis qu'un enseignant expérimenté (Cyril) développe des outils numériques (algorithmes, radar). Cela illustre qu'il n'y a pas une seule "bonne solution", mais que le choix dépend du "contexte qui nous organise" et de la "fibre d'enseignant".
      • L'outil Radar (Exemple en Natation Sauvetage) :Outil numérique pour "gagner en précision et gagner en temps" et "se libérer du temps pour être au contact de mes élèves".
      • Permet de travailler l'"éducation au choix" en lycée.
      • Simule des scénarios complexes (ex: sauvetage en mer avec clapot).
      • L'élève (et son observateur/tuteur) se positionnent sur quatre axes (indicateur d'impact scénario, mental, musculaire, respiratoire).
      • Cela "colore" l'"indicateur de compétence" central, indiquant le niveau d'engagement possible ("peut s'engager raisonnablement mais que ça reste difficile").
      • Aide l'élève à "séquencer sa prise de décision" en fonction de ses ressentis, pour dépasser l'émotionnel et prendre des décisions "réfléchie, la plus rationnelle possible" (s'engager ou renoncer), en lien avec le CA2.
      • Lien avec les "expériences corporées culturelles" (ECC2) du CRÈS et le "plaisir de pratiquer" (expériences mémorables à partager).
      • L'indicateur 2.0 (Exemple en Danse) :"Entremêle les trois fils" (moteur, méthodologique, social).
      • Utilise un score (ex: 1 10 100) pour révéler les "lignes de force" et les "obstacles".
      • Concept d'"aiguillage" : étayage (ressources extérieures) ou guidage (dépendant de l'enseignant) pour aider l'élève.
      • L'objectif est que l'élève "accepte de demander de l'aide à l'enseignant".
      • Exemple du 344 en danse en collège difficile : utilisation d'un score (unités = cadre de composition, dizaines = lisibilité de l'intention/motricité, centaines = effet sur le spectateur) pour identifier les besoins et proposer des situations d'apprentissage spécifiques (ex: "odsédomaire" pour créer un "moment fort" et gagner des points).
      • Dynamique des "3 CP" : clarifier, comprendre, se confronter pour progresser.
      • Apport méthodologique dynamisant le moteur et le social par une "observation outillée".
      • Relation d'"interdépendance fonctionnelle" : Moteur x Méthodologique x Social = Moteur au cube.
      • Focus sur l'"entraide" et l'"empathie" comme valeurs fondamentales. Utilisation d'outils pour communiquer "positivement et constructivement" sur des indicateurs précis.
      • Situations d'apprentissage purement sociales (Fil Vert Social) :Constat du manque d'apprentissage de l'arbitrage en tant qu'élève.
      • Plaidoyer pour des "situation d'apprentissage purement sociale" car on y gagne "à apprendre à nos élèves aussi à devenir arbitre".
      • L'objectif est de dépasser l'"insatisfaction professionnelle" liée au manque de compétence en arbitrage et la peur du jugement des pairs.
      • Utilisation d'outils numériques (PowerPoint, Rush) pour créer une "application" d'apprentissage de l'arbitrage en sport collectif (ex: Ultimate), avec des scénarios, un compte à rebours de réflexion, sélection de réponse et correction.
      • Cela crée une "interdépendance fonctionnelle" en créant le "besoin de l'autre", pas seulement parce que c'est institutionnel, mais parce qu'il y a un "intérêt" fonctionnel.
      • Mise en œuvre des "compétences psychosociales" (cognitif, émotionnel, social) dans le cadre des cours d'EPS.

      6. Préoccupations et Souhaits (Notamment sur les Inaptitudes)

      • Ce qui "gratte" et ce qui "pique" les enseignants : Le manque de respect "gratte", les "conduites d'évitement" et les inaptitudes "piquent".
      • Problème des inaptitudes et certificats médicaux : Constat de la facilité d'accès aux certificats médicaux (via la famille, etc.) et des "inaptitudes plus ou moins bien remplies". Ces certificats datent de 1989.
      • Souhait de renforcer les "aptitudes partielles".
      • Plaidoyer pour l'EPS "en plus" : Notamment pour les élèves qui en ont le plus besoin, mobilisant les heures d'accompagnement personnalisé, sur le modèle du "sport sur ordonnance" dans la société civile.
      • Exemple de la natation et des inaptitudes : Difficulté rencontrée avec les allergies au chlore, avec un taux d'inaptitude élevé en début d'année. Stratégie de proposer des cours en mer comme alternative.
      • Appel à l'aide / Souhait : Faire en sorte que la validation des inaptitudes sorte des mains du "médecin de famille qui est obligé de répondre aux attentes de ses clients" pour aller vers un "médecin dermatologue réel" (tests d'allergie) ou un "médecin du sport qui sera un peu plus regardant".

      7. Conclusion

      Le groupe ÉPIC propose une vision de l'EPS de demain centrée sur une évaluation au service des apprentissages, légitime, positive et compréhensible.

      Leur démarche, soutenue par des outils concrets, vise à stimuler la mobilisation des élèves en créant du sens, en favorisant l'autonomie et l'entraide, et en prenant en compte les dimensions motrice, méthodologique et sociale de la compétence de manière contextualisée. Ils soulignent l'importance de la collaboration avec d'autres acteurs de l'EPS et expriment des préoccupations quant aux défis rencontrés sur le terrain, notamment les questions de respect et de gestion des inaptitudes.

    1. // 2 cubicTo( x1 = height, y1 = 0f, x2 = height + cornerLength / 3, y2 = 0f, x3 = height + cornerLength, y3 = 0f )

      Interpolation - it's a function f(P1, P2, t) that gives you a point between 2 points for given t ∈ <0, 1> ( imagine you walk on path between point A and point B and you stop after you finished exactly 34,2353% of the whole road. To know what is your current point on path, you calculate interpolation f(A, B, 0.342353) )

      Polynomial interpolation - it's just a interpolation of two interpolations which are interpolations of two interpolations and on and on.... So quadratic interpolation is just a interpolation of two interpolations. (it's a situation when we have 3 points - cubic interpolation it's when we have 4 points)

      Quadratic Bezier curve - it's a curve drawn using interpolation of two interpolations (A -> B, A -> C)

      Cubic Bezier curve - it's a curve drawn using interpolation of two interpolations of two inteprolations 1st interpolations: A->B, B->C, C->D 2nd inteprolations: (A->B)->(B->C), (B->C)->(C->D) 3rd (final) interpolation: ((A->B)->(B->C))->((B->C)->(C->D))

      cubicTo(x1,x2,x3) - it's just drawing a cubic Bezier curve. You might ask, where is the fourth point? The fourth point is where you currently are on Path, it's a starting point.

    1. 七个原则:牺牲、真理、力量、美、生命、记忆和服从

      当然可以!我们来用更清晰、更通俗的方式理解**约翰·拉斯金(John Ruskin)在《建筑的七盏明灯》(The Seven Lamps of Architecture, 1849)中提出的思想。可以把这本书想象成他为建筑写的一份“精神宪章”,其中“七盏明灯”**就像是他心中的七个“指导原则”,为真正有灵魂、有道德的建筑指路。


      🕯️ 什么是“七盏明灯”?

      拉斯金认为,建筑不是冰冷的石头堆砌,而是能表达人类精神与道德价值的艺术形式。因此,好的建筑应该像人一样,有灵魂、有品格、有责任感。为此,他提出了建筑必须遵循的七条“精神准则”,他称之为**“七盏明灯”**:


      🕯️1. 牺牲(Sacrifice)

      核心思想: 建筑应体现对神明、祖先或精神信仰的尊敬,哪怕需要花费更多精力和成本。

      • 举例理解:古代的庙宇、教堂、陵墓等往往耗费巨大心血,不为实用,只为表达一种“敬畏之心”。
      • 拉斯金认为,真正的建筑是对“更高意义”的奉献,而非为了炫富或实用性设计。

      🕯️2. 真理(Truth)

      核心思想: 建筑必须诚实,不能欺骗;所用材料和结构要真实、不过度装饰。

      • 举例理解:如果柱子是装饰的,不是承重的,就不该假装它是承重的。
      • 拉斯金讨厌“假大空”的东西,认为建筑应该尊重材料、诚实表达功能

      🕯️3. 力量(Power)

      核心思想: 建筑应展现一种“存在感”,像自然界的山峦一样令人震撼和崇敬。

      • 他特别推崇哥特式教堂那种直刺苍穹的力量感,能激发人的信仰与情感。
      • 不是“肌肉”那种力量,而是一种精神的雄浑与雄伟。

      🕯️4. 美(Beauty)

      核心思想: 建筑要有真正的美感,这种美感来自自然、来自匠心、来自真诚的装饰。

      • 拉斯金认为,美不是“对称+金闪闪”,而是精细工艺、人与自然的和谐
      • 哥特式建筑中的雕刻、花窗,哪怕是细节处的动物,都是真正的人文美。

      🕯️5. 生命(Life)

      核心思想: 建筑要体现工匠的手工劳动、创作自由和个性,而不是冷冰冰的机器复制。

      • 他反对工业时代的“标准化建造”,认为机械化会扼杀工匠的创造力
      • 每一块石雕,每一个窗棂都应该能看出工匠的“灵魂”。

      🕯️6. 记忆(Memory)

      核心思想: 建筑要尊重历史,体现文化传承,成为人类记忆的容器。

      • 古老的建筑不该被轻易推倒;建筑应该传递时代的精神
      • 他认为,建筑是一种“石头写成的历史书”。

      🕯️7. 服从(Obedience)

      核心思想: 建筑应尊重传统,不可过度标新立异,要在已有文化中谦逊创新。

      • 他反对那种自我狂妄式的“炫技建筑”,强调建筑师要在传统中工作,而不是踩着传统炫耀自己

      🏰 为什么他特别推崇哥特式建筑?

      • 哥特建筑体现了上述所有精神:宗教情怀(牺牲)、真实材料(真理)、尖塔与飞扶壁的力量感(力量)、细致雕刻(美)、手工精神(生命)、历史延续(记忆)、传统延续(服从)。
      • 他认为哥特式教堂是建筑的“灵魂巅峰”,体现了人类在信仰、劳动与美感上的极致努力。

      🧠 小结一句话版本:

      拉斯金通过“七盏明灯”告诉我们:建筑不只是房子,而是人类精神、信仰与劳动的凝结体;不是靠炫技,而是靠真诚、传统与意义活下来的艺术。


      如果你想把这些原则应用在现代建筑、设计或文化评论中,我可以继续展开对应的类比或案例!

    1. Author response:

      The following is the authors’ response to the previous reviews

      Reviewer #1 (Public Review):

      Batra, Cabrera and Spence et al. present a model which integrates histone posttranslational modification (PTM) data across cell models to predict gene expression with the goal of using this model to better understand epigenetic editing. This gene expression prediction model approach is useful if a) it predicts gene expression in specific cell lines b) it predicts expression values rather than a rank or bin, c) if it helps us to better understand the biology of gene expression or d) it helps us to understand epigenome editing activity. Problematically for point a) and b) it is easier to directly measure gene expression than to measure multiple PTMs and so the real usefulness of this approach mostly relates to c) and d).

      We appreciate this point from Reviewer #1 and the instructive comments and helpful feedback on our study. We designed our approach keeping in mind that the primary use case is to understand how epigenome editing would affect gene expression.

      Other approaches have been published that use histone PTM to predict expression (e.g. PMID 27587684, 36588793). Is this model better in some way? No comparisons are made although a claim is made that direct comparisons are difficult. I appreciate that the authors have not used the histone PTM data to predict gene expression levels of an "average cell" but rather that they are predicting expression within specific cell types or for unseen cell types. Approaches that predict expression levels are much more useful whereas some previous approaches have only predicted expressed or not expressed or a rank order or bin-based ranking. The paper does not seem to have substantial novel insights into understanding the biology of gene expression.

      We thank Reviewer #1 again for this insightful comment. We have included citations for a series of papers (PMIDs: 27587684, 30147283, 36588793) that performed gene expression prediction using histone PTM data. However, each of these methods performs classification of gene expression as opposed to predicting the actual gene expression value via regression. Additionally, the referenced studies all work with Roadmap Epigenomics read-depth data as opposed to p-values obtained from the ENCODE pipelines, making it difficult to make direct comparisons. We outline in the Discussion section that by creating a comprehensive dataset of epigenome editing outcomes, which include quantification of histone PTMs before and after in situ 1 perturbations, will improve our understanding of the effects of dCas9-p300 on gene expression and assist in the design of gRNAs for achieving fine-tuned control over gene expression levels. In this revised version of our study, we have also added new data (Figure 3 – figure supplement 3) to further benchmark our model against others.

      The approach of using this model to predict epigenetic editor activity on transcription is interesting and to my knowledge novel although only examined in the context of a p300 editor. As the author point out the interpretation of the epigenetic editing data is convoluted by things like sgRNA activity scoring and to fully understand the results likely would require histone PTM profiling and maybe dCas9 ChIP-seq for each sgRNA which would be a substantial amount of work.

      We agree with the Reviewer and view these experiments as important components of future studies.

      Furthermore from the model evaluation of H3K9me3 is seems the model is performing modestly for other forms of epigenetic or transcriptional editing- e.g. we know for the best studied transcriptional editor which is CRISPRi (dCas9-KRAB) that recruitment to a locus is associated with robust gene repression across the genome and is associated with H3K9me3 deposition by recruitment of KAP1/HP1/SETDB1 (PMID: 35688146, 31980609, 27980086, 26501517).

      This is an interesting point. We have included new data (Figure 4 – figure supplement 1), that quantifies how sensitive the trained gene expression model is to perturbations in H3K9me3. Indeed our data suggests that the model predictions are sensitive to perturbations in H3K9me3. For instance, there is a clear decrease and a gradual increase as the position where the perturbation is performed moves from upstream to downstream of the TSS. Additionally, the magnitude of the predicted fold-change is a function of how much the H3K9me3 is perturbed and hence the magnitude of change would be even higher if the perturbation magnitude is increased. However, this precise magnitude is hard to estimate In the absence of experimental perturbation data for H3K9me3. Leveraging our model in combination with KRAB-based CRISPRi is an exciting and important aspect of future studies.

      One concern overall with this approach is that dCas9-p300 has been observed to induce sgRNA independent off target H3K27Ac (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8349887/ see Figure S5D) which could convolute interpretation of this type of experiment for the model.

      This remains an excellent point and indeed, we and others have observed that dCas9-p300 can result in off-target H3K27ac levels (both increased and suppressed) across the genome. Our study focused on p300, because the molecule is one of the few known proteins that can catalyze H3K27ac in the human genome, and H3K27ac remains a proxy for active genomic regulatory elements. Nevertheless, any off target activity of dCas9-p300 could certainly convolute our analyses. We have included language to address this caveat in our discussion.

      Reviewer #2 (Public review):

      Summary:

      The authors build a gene expression model based on histone post-translational modifications, and find that H3K27ac is correlated with gene expression. They proceed to perturb H3K27ac at 13 gene promoters in two cell types, and measure gene expression changes to test their model.

      We remain appreciative of the constructive feedback and input from Reviewer #2 on our manuscript.

      Strengths:

      The combination of multiple methods to model expression, along with utilizing 6 histone datasets in 13 cell types allowed the authors to build a model that correlates between 0.7-0.79 with gene expression. They use dCas9-p300 fusions to perturb H3K27ac and monitor gene expression to test their model. Ranked correlations of the HEK293 data showed some support for the predictions after perturbation of H3K27ac.

      Weaknesses:

      The perturbation of 5 genes in K562 with perturb-seq data shows a modest correlation of ~0.5 and isn't included in the main figures. The authors are then left to speculate reasons why the outcome of epigenome editing doesn't fit their predictions, which highlights the limited value in the current version of this method.

      We agree with the reviewer’s suggestion and highlight in our conclusion that generating epigenome editing data across a variety of cell types and across many genes will help uncover the underlying mechanisms of gene expression modulation.

      As mentioned before, testing genes that were not expressed being most activated by dCas9-p300 weaken the correlations vs. looking at a broad range of different gene expression as the original model was trained on.

      We appreciate this comment from Reviewer #2. We note that the data generated from this dCas9-p300 perturb-seq experiment used gRNAs from a pre-existing library published previously (PMID: 37034704). While this library enabled deeper interrogation of dCas9-p300 driven effects compared to our previous revision, the gRNAs in this library were designed against genes associated with haploinsufficiency in neuronal cell types, and which were generally lowly-expressed in K562 cells. Further, we restricted our analysis here to promoter-proximal gRNAs (as opposed to enhancer-targeted gRNAs in the library), focusing our scope even more so. Thus the genes ultimately used for analysis are enriched for low expression.

      If the authors want this method to be used to predict outcomes of epigenome editing, expanding to dCas9-KRAB and other CRISPRa methods (SAM and VPR) would be useful. Those datasets are published and could be analyzed for this manuscript.

      This is an exciting suggestion from Reviewer #2. We agree, and view this as a component of future work in this area.

      The authors don't compare their method to other prediction methods.

      In this revised version of our study, we have also added new data (Figure 3 – figure supplement 3) to further benchmark our model against others. These data demonstrate that our CNN model outperforms existing approaches across multiple cell types.

      Recommendations for the authors:

      Reviewer #2 (Recommendations for the authors):

      Looking at the individual genes in K562 shows a random looking range of predictions and observed, with the exception of Bcl11A which is one of two genes in this set of 5 that are not expressed. I will repeat my earlier comment, that epigenome editing and CRISPRa methods generally show the most upregulation with the lowest expressed genes. I speculate that plotting endogenous expression vs. outcome (assuming using all gRNAs within a reasonable and similar distance to TSS) would produce a correlation of -0.5 or greater and be as useful as this method.

      We agree, and believe that this demonstrates more work is needed in this emerging research area.

      The methods describe Perturb-seq analysis but not the bench experiments.

      We have added the bench methods related to our Perturb-seq experiments to our revised manuscript under the Experimental Methods section in the Appendix.

      I don't understand why the authors can't compare to other methods as that is fairly standard in new prediction papers. I get that others used REMC vs. ENCODE, and were rank or binary based, but the authors could use REMC data and/or convert their data to ranked or binary and still compare. Lacking that it's hard to judge this manuscript.

      We have added benchmarking against existing methods as Figure 3 – figure supplement 3.

    1. Got the game from Kane, Wayne se bling

      "Got the game from Kane, Wayne से bling"

      1. "Kane" = likely refers to Big Daddy Kane, a pioneer of 80s–90s lyrical rap — Raftaar salutes OG lyrical technique here.

      2. "Wayne से bling" = Lil Wayne, the bling era, punchlines, and swagger-filled wordplay — he took style from Wayne, substance from Kane.

      3. Duality shown here: Knowledge from Kane, flash from Wayne — bars + buzz.

      4. Subliminal flex: He didn’t just mimic desi rappers — he studied the game from the source.

    1. Author response:

      The following is the authors’ response to the previous reviews

      Our revised manuscript thoroughly addresses all comments and suggestions raised by the reviewers, as detailed in our point-by-point response. To strengthen our findings, we have conducted additional in vivo experiments to evaluate the presence of fibro-adipogenic progenitors (FAPs) at different time points during HO formation in control and BYL719-treated mice. Our results indicate that BYL719 reduces the accumulation of FAPs and promotes muscle fiber regeneration in vivo. We have also expanded our discussion on BYL719’s effects on mTOR signaling, further clarifying key points raised by Reviewer #1, and have addressed all minor comments.

      Additionally, in response to Reviewer #2, we have employed an orthogonal and complementary approach using a new model. We conducted chondrogenic differentiation experiments with murine MSCs expressing either ACVR1wt or ACVR1<sup>R206H</sup>. qPCR analysis of chondrogenic gene markers (Sox9, Acan, Col2a1) demonstrates that Activin A enhances their expression in ACVR1<sup>R206H</sup> cells, whereas BYL719 strongly suppresses their expression, regardless of ACVR1 mutational status. These new data further confirm that BYL719 effectively inhibits genes involved in ossification and osteoblast differentiation, independent of the ACVR1 mutation. We have also expanded our discussion to further clarify points raised by Reviewer #2 and have addressed all remaining minor comments.

      Below, we provide a detailed point-by-point response to the reviewers’ comments:

      Rreviewer #1:

      Point 1: In this revised manuscript, the authors clearly showed that BYL719 suppressed the proliferation and differentiation of murine myoblasts, C2C12 cells, in addition to human MSCs in vitro. Furthermore, BYL719 decreased migratory activity in vitro in monocytes and macrophages without suppressing proliferation. Overall, these data suggested that BYL719 is not a specific chemical compound for cell types or signaling pathways as mentioned in the manuscript by the authors themselves. Therefore, it was still unclear how to explain the molecular mechanisms in inhibition of HO by the compound in a specific signaling pathway in a specific cell type, MSCs, contradicting many other possibilities. The authors should add logical explanations in the manuscript.

      Regarding its selectivity, BYL719 is a potent and highly selective inhibitor of PI3Kα. It has been demonstrated in multiple studies and in several in vitro kinase assay panels (Furet et al. PMID: 23726034, Fritsch et al. PMID: 24608574). The IC50 or Kd values for BYL719 against PI3Kα were at least 50 times lower than for most of other kinases tested. Moreover, BYL719 is also highly selective for PI3Kα (IC50 = 4.6 nmol/L) compared to other class I PI3K (PI3Kβ (IC50 = 1,156 nmol/L), PI3Kδ (IC50 = 290 nmol/L), PI3Kγ (IC50 = 250 nmol/L)) (Fritsch et al). Consistent with these data, we show that, at the concentrations tested, BYL719 does not have a direct effect on any kinase receptor within the TGF-b superfamily, including ACVR1 or ACVR1<sup>R206H</sup>.

      Rather than blocking ACVR1 kinase activity, in our manuscript we provide evidence that BYL719 has the potential to inhibit osteochondroprogenitor specification and prevent an exacerbated inflammatory response in vivo (Valer et al., 2019a PMID: 31373426, and this manuscript) through different mechanisms, such as (i) increasing SMAD1/5 degradation, (ii) reducing transcriptional responsiveness to BMPs and Activin, (iii) blocking non-canonical ACVR1 responses such as the activation of AKT/mTOR. All these defined molecular mechanisms contribute to suppress HO in vitro and in vivo, as we report and explain throughout the manuscript. Selective PI3Kα inhibition is at the core of the different molecular pathways described. As such, PI3Kα blockade inhibits the phosphorylation of GSK3 and compromises SMAD1 protein stability, thereby altering canonical responsiveness and osteochondroprogenitor specification (Gamez et al PMID: 26896753; Valer et al PMID: 31373426). Moreover, PI3Kα blockade downregulates Akt/mTOR signalling, which is critical for FOP and non‐genetic (trauma induced) HO in preclinical models (Hino et al, 2017 PMID: 28758906; Hino et al. PMID: 30392977). Finally, PI3Kα inhibition hampers a number of proinflammatory pathways, thereby limiting the expression of pro-inflammatory cytokines, reducing the proliferation of monocytes, macrophages and mast cells, and partially blocking the migration of monocytes. As we suggest in the discussion of the manuscript, this effect likely causes a poor recruitment of monocytes and macrophages at injury sites and throughout the in vivo ossification process.

      Noteworthy, in our manuscript we do not refer to a “specific chemical compound for cell types”. Rather, in the Discussion we write “the administration of BYL719 prevented an exacerbated inflammatory response in vivo, possibly due to specific effects observed on immune cell populations.” This sentence did not intend to imply that BYL719 only affects these specific cell types, but aimed to emphasize the effects observed on those cell populations, even though systemic BYL719 may affect all populations. We rephrased it to “the administration of BYL719 prevented an exacerbated inflammatory response in vivo, possibly due to the effects observed on immune cell populations.” to provide a clearer message as suggested by the reviewer. We thank the reviewer for these questions and hope that these explanations and changes in the text improve the clarity of the message.

      Mesenchymal stem/stromal cells (MSCs) are osteochondroprogenitor cells that can follow distinct differentiation paths. In this study, we use these cells as an in vitro model for the study of osteochondrogenitor specification. MSCs, and induced MSCs (iMSCs), have been widely used as in vitro cellular models of osteochondroprogenitor specification for the analysis of markers, signaling, modulation, and differentiation potential or capacity. Their use as models for this purpose has been extensively studied in wild type MSCs, and in the presence of FOP mutations (Boeuf and Richter PMID: 20959030; Schwartzl et al. PMID: 37923731).

      Point 2: Related to comment #1, the effects of BYL719 on the proliferation and differentiation of fibro-adipogenic cells in skeletal muscle, which are potential progenitor cells of HO, should be important to support the claim of the authors.

      We have performed additional in vivo experiments to assess the presence of fibro-adipogenic precursors (FAPs) at different time-points during HO formation in control and BYL719-treated in the mouse model of heterotopic ossification. We analyzed the number of fibro-adipogenic progenitor (FAPs) during the progression of the HO. These data are shown in the new Figure3-Figure Supplement 1. We demonstrate that BYL719 reduces the number of PDGFRA+ cells (FAPs, red) throughout the ossification process in vivo. Moreover, now we also show an enlargement of the diameter of myofibers (labelled with wheat germ agglutinin, green) when animals were treated with BYL719, indicating improved muscle regeneration and further validating the data reported as supplementary figures that were added in the first revision of this manuscript.

      Point 3: BYL719 inhibited signaling through not only ACVR1-R206H and ACVR1-Q207D but also wild type ACVR1 and suppressed the chondrogenic differentiation of parental MSCs regardless of the expression of wild type or mutant ACVR1. Again, these findings suggest that BYL719 inhibits HO through a multiple and nonspecific pathway in multiple types of cells in vivo. The authors are encouraged to explain logically the use of bone marrow-derived MSCs to examine the effects of BYL719.

      As detailed in main point 1, we consider that the main target, molecular mechanisms and inhibited pathways by BYL719 are specific and well characterised in other research articles and further defined in this manuscript, including the generation of PI3Ka deficient mice in an FOP background, that undoubtedly demonstrates an essential role for PI3Ka in ACVR1-driven heterotopic ossification in vivo. Altogether, we are confident that BYL719 inhibits HO through multiple and specific pathways that arise from the PI3Kα inhibition. As a systemically administrated drug, BYL719 affects the multiple types of cells in vivo that express PI3Kα. It is well known that PI3Kα is exquisitely required for chondrogenesis and osteogenesis (Zuscik et al. PMID; Gamez et al PMID: 26896753 1824619). Accordingly, throughout the manuscript we refrain from suggesting a specific effect on ACVR1-R206H cells but instead an inhibitory effect on cell number and differentiation regardless on the ACVR1 form expressed.

      Similarly, as detailed in main point 1, MSCs and hiPSCs have been extensible used as in vitro cellular models of osteochondroprogenitor specification for the analysis of markers, signaling, modulation, and differentiation potential or capacity (Barruet et al., PMID: 28716551; Kan et al., PMID: 39308190).

      Point 4: BYL719 clearly inhibits an mTOR pathway. Is there a possibility that BYL719 suppresses HO by inhibiting mTOR rather than PI3K? The authors are encouraged to show the unique role of PI3K in BYL719-suppressed HO formation.

      As clarified above, BYL719 is a potent and selective inhibitor of PI3Kα, with minimal off-target inhibition against other kinases, as it has been demonstrated in multiple studies and in several in vitro kinase assay panels. In the same study, while IC50 of BYL719 against PI3Kα was (IC50 = 4.6 nmol/L), IC50 against mTOR was (IC50= >9,100 nmol/L), indicating that it was not directly inhibited. mTOR is one of the well-known pathways that are activated downstream of PI3K. Therefore, there is no surprise that blocking PI3Kα will block mTOR signalling. This potential effect was already demonstrated in previous publications (Valer et al., 2019a PMID: 31373426) and discussed throughout the first revision. We consider that the additive effect of mTOR inhibition and other molecular mechanisms downstream of PI3Kα, including reduced SMAD1/5 protein levels, contribute to the in vivo HO inhibition by BYL719.

      Reviewer #2:

      Point 1: It is also important to note that, in most of the data, there is no significant difference between cells with wild-type ACVR1 and those with the R206H mutation. The authors demonstrated that ACVR1 is not a target of BYL719 based on NanoBRET assay data, suggesting that BYL719's effect is not specific to FOP cells, even though they used an FOP mouse model to show in vivo effects.

      The main effect of R206H mutation is the gain of function in response to Activin A. For most of the responses to other ACVR1 ligands (e.g. BMP6/7), we observe a slightly increased response in the presence of the mutation (which is consistent with previous research, usually labelling RH as a “weak activating mutant” unless Activin A is added (Song et al., PMID: 20463014)). Therefore, as expected, most of the differences between WT and RH mutant cells can be observed mostly upon Activin A addition, as observed, for example, in Figure 3 of our manuscript.

      We agree with the reviewer that, at the concentrations used, BYL719 does not specifically target FOP cells. However, we believe that it targets downstream pathways of PI3Kα inhibition that are essential for osteochondrogenic specification, regardless of mutation status. This therapeutic strategy aligns with other experimental drugs, including Palovarotene (validated for FOP) and Garetosmab and Saracatinib (in advanced clinical trials), which target Activin A function, ACVR1 activity, or osteochondrogenic differentiation irrespective of the mutant allele. Unlike these molecules, BYL719 has been chronically administered to patients (including children) without major side effects (Gallagher et al.; PMID: 38297009), further supporting its potential for safe long-term use.

      The authors should consider that the effect of Activin A on R206H cells is not identical to that of BMP6 on WT cells. If the authors aim to identify the target of BYL719 in FOP cells, they should compare R206H cells treated with Activin A/BYL719 to WT cells treated with BMP6/BYL719.

      We use Activin A and BMP6, both high-affinity ACVR1 ligands, to demonstrate, as observed in figure 6, that PI3Kα inhibition can inhibit the expression of genes within GO terms ossification and osteoblast differentiation. It is important to note, however, that Activin A canonical signaling receptor is ACVR1B. Since BYL719 blocks the induction of a heterotopic ossification gene expression signature common to Activin A and BMP6, in the context of the FOP mutation R206H, our results indicate that BYL719 inhibition affects a signaling pathway downstream of ACVR1, activated by either BMP6 (wild type receptor, relevant for non-genetic heterotopic ossifications) or Activin (R206H mutant receptor, relevant for FOP).

      We consider that the comparison (RH ACTA BYL vs WT BMP6 BYL) would provide confounding results raised from intrinsic model differences in basal expression programs (WT vs RH), and differences in the quantitative level of signaling of the different ligands at these specific doses. First, if we only consider SMAD1/5 signaling, Activin A and BMP6 won’t have identical signaling, and differences will arise from the strength of that signaling. Secondly, in the suggested comparison we would find, mostly, all the differential gene expression promoted by Activin A canonical signaling through type I receptors ACVR1B/ALK4 in complex with ACVR2A or ACVR2B, promoting SMAD2/3 activation (in addition to the altered signaling that ACVR1-R206H could promote). Examples of differential response in pSMAD1/5 in ACVR1-WT or RH with BMP ligands and R206H with Activin A ligand, and examples of pSMAD2/3 canonical signaling in R206H cells have been described in Ramachandran et al, PMID: 34003511; Hatsell et al., PMID: 26333933).

      Point 2: The interpretation of the data in the new Figure 5 is inappropriate. Based on the expression levels of SOX9, COL2A1, and ACAN, it is unclear whether the effect of BYL719 is due to the inhibition of differentiation or proliferation. The addition of Activin A showed no difference between ACVR1/WT and ACVR1/R206H cells, suggesting that these cells did not accurately replicate the FOP condition.

      To gain consistency in our manuscript, we decided to use an orthogonal and complementary approach in a completely new model. We performed new experiments of chondrogenic differentiation using murine MSCs from UBC-Cre-ERT2/ACVR1<sup>R206H</sup> knock-in mice. These cells, when treated with 4OH-tamoxifen, express the intracellular exons of human ACVR1<sup>R206H</sup> in the murine Acvr1 locus. Therefore, we can compare differentiation of wild type and R206H MSCs isolated form the same mice. We initiated the chondrogenic differentiation assay from confluent cells to minimize changes in cell proliferation throughout the process. These new results are shown in the new Figure 5F. Mutant (RH) cells display an enhanced chondrogenic response to activin A compared to wild type cells. The treatment with BYL719 decreased the expression of chondrogenic markers irrespective of the mutational status of ACVR1 in the cells, further supporting our previous results in this manuscript and published article (Valer et al., 2019a PMID: 31373426).

      Point 3: The additional investigation of RNA-seq data provided useful information but was insufficient to fully address the purpose of this study. The authors should identify downregulated genes by comparing WT cells treated with Activin A/BYL719 and Activin A alone and then compare these identified genes with those shown in Figure 5E. Additionally, they should compare R206H cells treated with Activin A/BYL719 to WT cells treated with BMP6/BYL719. These comparisons will clarify whether there are FOP-specific BYL719-regulated genes.

      We thank the reviewer for considering that RNAseq data provides useful information. As already discussed in our answer above, our results indicate that regardless of the ligand (Activin A or BMP6) and regardless of the ACVR1 mutation (WT, relevant for non-genetic heterotopic ossifications or RH, relevant for FOP), BYL719 can inhibit the expression of the genes relevant to endochondral ossification. In our opinion, this is a very relevant conclusion of this study.

      We have deeply considered the strategy proposed by the reviewer, comparing “WT cells treated with Activin A/BYL719 and Activin A alone and then compare these identified genes with those shown in Figure 5E” and/or comparing “R206H cells treated with Activin A/BYL719 to WT cells treated with BMP6/BYL719”. While we have discussed why we do not consider appropriate the first comparison proposed, there are a number of reasons why we are not confident that the second comparison would provide a straightforward conclusion.

      Regarding the second suggested comparison already in Main point 1, we consider that it would provide confounding results due to all the arguments detailed in Main point 1. Regarding the first suggested comparison, we also consider that it would provide confounding results. There are several reasons why we do not consider that the genes only found in the RH comparison can be confidently considered genes that are only affected by BYL719 in RH cells.

      First, the effect of BYL719 in an osteogenic-prone sample (for example, RH-ActA) is higher than the effect that we can observe in absence of this activation (for example, WT-ActA), as observed in the higher number of significantly downregulated genes in RH ActA BYL vs RH ActA comparison, compared to WT ActA BYL vs WT ActA. Similar results are observed in figure 3C, where the expressions of the genes are significantly inhibited in RH ActA compared to RH ActA BYL. This inhibition is not significantly observed in in WT ActA compared to WT ActA BYL because the osteogenic expression of these genes is already very weak in the absence of ACVR1 R206H. This weak signaling of pSMAD1/5 in the absence of osteogenic signaling (RH without ligand or, especially, WT with Activin A) has already been described (Ramachandran et al. MID: 34003511). Therefore, even though the inhibition is present in both comparisons, as observed in figure 6C, the extent of the observed effect is different. Second, we are comparing a different number of DEGs for each comparison between them. If we compare the 67 downregulated genes from one comparison and 38 downregulated genes from the other comparison, the unequal list size may inflate the number of unique genes in the group with more downregulated genes. To prove these concerns, we performed the comparison that the reviewer suggested and we found, for example, that amongst the 38 differentially downregulated ossification genes in (WT_ActA_BYL vs WT_ActA) and 67 differentially downregulated ossification genes in (RH_ActA_BYL vs RH_ActA), 39 genes were only found in the RH comparison, while 10 were only found in the WT comparison, and 28 were found in both.

      These effects are present, for example, when studying the ID genes, well-known downstream mediators of BMP signaling. In this case, ID1 is downregulated in both comparisons, while ID2, ID3, and ID4, are downregulated only in the RH-group, despite the fact that all ID1, ID2, ID3, and ID4 are similarly regulated and increase their expression with similar time curves upon BMP signaling activation (Yang et al., PMID: 23771884). Therefore, we consider that the comparisons proposed will not help us to identify specific BYL719-regulated genes relevant for FOP and/or ACVR1 R206H signaling. Again, we consider that BYL719 effect is not specific of FOP cells. Our results show that regardless of the ligand (Activin A or BMP6) and regardless of the ACVR1 mutation (WT, relevant for non-genetic heterotopic ossifications or RH, relevant for FOP), BYL719 can inhibit the expression of the genes linked to ossification and osteoblast differentiation, which could be important for the treatment of FOP and non-genetic heterotopic ossifications.

      Point 4: The data in Figure 7 are not relevant to the aim of this study because the cell lines used in these experiments did not have ACVR1/R206H mutations. The authors mentioned that BMP6 is a ligand for ACVR1 and, therefore, these experiments reflect the situation of inflammatory cells in FOP. This is inappropriate and not rational. As mentioned above, the effect of Activin A on FOP cells is not identical to the effect of BMP6 in wild-type cells. The data in Figure 7 indicated that the effect of BYL719 is unrelated to the presence of BMP6, clearly demonstrating that these experiments are not related to the activation of ACVR1. In the gene expression analyses, almost all genes showed no changes with the addition of BMP6. Only TGF and CCL2 showed upregulation in THP1 cells, and the treatment with BYL719 failed to inhibit the effect of BMP6, suggesting that these experiments merely demonstrate the effect of BYL719 on inflammatory cells irrespective of the presence of the HO signal.

      We consider that Figure 7 is relevant to the aim of this study. As shown in Fig. 8, treatment of FOP mice with BYL719 led to a decreased recruitment of immune cells within the FOP lesions, suggesting a direct effect of BYL719 in immune cells. This is very relevant for the FOP pathology, since flare-ups have been linked with inflammatory episodes since the very early characterization of the disease (Mejias-Rivera et al., PMID: 38672135). Given the technical difficulties to transduce THP1, RAW264 and HMC1 cell lines with lentiviral particles carrying ACVR1 R206H, we decided to partially recapitulate ACVR1 R206H activation with recombinant BMP6 and to test the effect of BYL719 in these conditions. In these models, we found that BYL719 inhibited the expression of key genes driving immune cell activation, in a cell-type and ligand independent manner. To clarify this rationale, we have swapped Figures 7 and 8 and adjusted our conclusions accordingly. We have softened our interpretations, emphasizing the absence of the ACVR1 R206H mutant receptor in these experiments.

    1. Er zijn drie onderscheidende dimensies van deze organisatorische normen: * Content: wat als belangrijk wordt gezien * Consensus: in welke mate deze normen gedeeld worden door leden van de organisatie * Intensity: de intensiteit van de gevoelens over het belang van een norm

      Een studie naar de organizational culture van 15 organisaties (in vier verschillende dienstensectoren) suggereert dat er zeven kenmerken van cultuur zijn:

      Innovation and risk taking Attention to detail Outcome orientation People orientation Team orientation Aggressiveness (vs. easygoingness) Stability

      Transparency betekent dat een bedrijf open en eerlijk is over zijn plannen en operaties, en dat werknemers open en eerlijk zijn tegenover elkaar en klanten. Vier redenen waarom dit belangrijk is: hogere werknemerproductiviteit, grotere betrokkenheid, hogere retentie en hogere klanttevredenheid.

      Goal incongruence en performance ambiguity beïnvloeden de behoefte aan controle binnen organisaties:

      Bij goal incongruence zijn leden het niet eens over de doelen. Performance ambiguity betekent dat inkomstenstromen onvoorspelbaar of onbekend zijn.

      Er zijn drie vormen van controle:

      Market control: prijzen vormen sociale interacties. Bureaucratic control: regels en procedures bepalen interacties. Clan control: gedeelde waarden en overtuigingen bepalen interacties.

      Bij clan control is de betrokkenheid van medewerkers het hoogst omdat zij de waarden van de organisatie hebben geïnternaliseerd. Deze controlevorm is kostenefficiënter, maar kan sociale druk en uitsluiting veroorzaken bij afwijking.

      Bij bureaucratic control zijn regels en monitoring duur, maar selectie is goedkoop. Bij clan control is selectie duurder, maar minder monitoring vereist.

      National Culture and Organizational Culture Uit de GLOBE-studies blijkt dat national culture (zoals machtsafstand en collectivisme vs. individualisme) een sterke invloed heeft op organizational culture. Er zijn vier belangrijke waarden: -Adaptability – vermogen om marktvraag te vertalen naar acties ➔ Voorspelt beste groei en innovatie -Involvement – vorming van menselijk vermogen, verantwoordelijkheid ➔ Voorspelt beste innovatie -Mission – betekenisvolle lange termijn richting ➔ Voorspelt winstgevendheid en groei -Consistency – waarden en subsystemen die sterke cultuur ondersteunen ➔ Ook gekoppeld aan winstgevendheid

      Binnen een organisatie bestaan drie subcultures: -Operators – productie, dienstverlening, klantinteractie -Engineers – systemen creëren om operaties te ondersteunen -Executives – financieel verantwoordelijk, beslissers

      Wanneer medewerkers het eens zijn over waarden en daar sterk in geloven, bestaat een strong organizational culture.

      Socialization Organizational socialization verwijst naar een proces waarbij een organisatie ervoor zorgt dat een nieuw lid alle noodzakelijke houdingen, gedragingen, kennis en vaardigheden verwerft om een productief lid van de organisatie te worden. De eerste zes maanden in een nieuwe baan worden gekenmerkt door een reeks reality-“shocks” terwijl de nieuwe medewerker wordt blootgesteld aan ongeschreven regels die de organizational culture definiëren. Het proces verloopt als volgt: Anticipatory socialization (zoeken naar een organisatie) →entry and assimilationmetamorphosis outcomes (werkprestaties, tevredenheid, betrokkenheid, lager verloop).

      Preentry verwijst naar de tijd tussen het aanbod en de start van het werk. In deze fase krijgt de medewerker informatie over de baan, die anders kan zijn dan in het sollicitatieproces werd voorgespiegeld. Ook speelt impression management een rol omdat nieuwe medewerkers zich zorgen maken over hoe ze worden waargenomen. Bestaande medewerkers observeren hen op geschiktheid, wat tot onrealistische verwachtingen kan leiden.

      Tijdens de entry-fase begint de medewerker echt met werken. Nieuwe medewerkers worden in de organizational culture opgenomen, soms via een formeel oriëntatieprogramma. Leidinggevenden spelen een belangrijke rol in het helpen van nieuwe medewerkers.

      De laatste fase heet metamorphosis. Dit is de overgang van nieuwe medewerker naar gewaardeerde collega. Ze hebben nu de organizational culture, regels en normen geïnternaliseerd.

      Succesvolle metamorphosis leidt tot hogere betrokkenheid, betere prestaties en tevredenheid. Bij promotie kan het hele proces opnieuw beginnen.

      Attraction-Selection-Attrition (ASA) Volgens de ASA-benadering voelen mensen zich aangetrokken tot organisaties die bij hun persoonlijkheid passen (goede PO fit). Dit betekent dat medewerkers die ervoor kiezen om ergens te werken vaak al dezelfde waarden delen (attraction-selection). Wanneer er een mismatch is tussen persoonlijke en organisatiewaarden, leidt dat tot turnover (intentie om te vertrekken). Daarom letten organisaties en sollicitanten op de ‘culture fit’ bij werving, vooral bij banen met hoog verloop.

      How Employees learn Culture Als onderdeel van het socialization-proces leert een medewerker ook over de organizational culture. Dat gebeurt via verhalen, rituelen, symbolen en taal.

      Storytelling betreft het delen van kennis en ervaringen die helpen om het werk te begrijpen. Verhalen bieden betekenis, inzicht en leiden gedrag.

      Ritual is een gestileerde sociale actie, zoals ceremonies of evenementen die de waarden van de organisatie tonen.

      Symbols zijn beelden, diagrammen of objecten die een culturele waarde of idee vertegenwoordigen. Voorbeeld: een CEO met een “open deur”-beleid staat symbool voor transparantie.

      Language verwijst naar de termen en jargon die de organisatie gebruikt. Bijvoorbeeld: medewerkers worden “teamleden” genoemd, of klanten “gasten” (zoals in Disneyland).

      Er is een duidelijk verschil tussen organizational culture (veranderend en historisch gegroeid) en organizational climate (huidige situatie). Culture legt nadruk op aannames en waarden, climate op waarneming.

      Climcult-perspectief: mensen nemen zowel cultuur als climate in acht als ze oordelen maken over hun werk omgeving

      ethical climate beïnvloed door moreel leiderschap. Wanneer leidinggevenden ethisch gedrag tonen, leidt dit tot hogere tevredenheid, betrokkenheid en minder turnover en verzuim. Vijf aspecten van ethical climate: zorgzaamheid, wet- en regelgeving, regels, instrumenteel, onafhankelijkheid.

      H 15 leading change and stress management Forces Driving Organizational Change Er zijn verschillende krachten die organizational change beïnvloeden: Workforce diversity – geslacht, ras, etniciteit, LGBTQ, leeftijd Economy – recessies, overheidsbeleid, gezondheidszorgkosten Technology – mobiele apparaten, sociale media, internetveiligheid, robotica Globalization – multinationals, politieke instabiliteit, eerlijke handel Competition – wereldwijde concurrentie, fusies, overnames, klantstandaarden Life-threatening events – natuurrampen, terrorisme, pandemieën

      Organisaties gaan ook over naar flexibelere werktijden, wat grote culturele verschuivingen veroorzaakt.

      Meest intense vorm = proactive + radical (transformation)

      Vier betrokken subsystemen in planned organizational change: Formal organization – structuur en beloningssysteem Dit zorgt voor coördinatie en controle tijdens de verandering Social factors – teaminteracties, cultuur Technology – input-naar-output processen: workflow design en job design Physical setting – karakteristieken van de fysieke omgeving

      -Sustainability – triple bottom line: Profit – financiële prestaties People – sociale verantwoordelijkheid Planet – milieuvriendelijkheid

      Force Field Analysis: krachten vóór en tegen verandering analyseren en actieplan maken.

      Kotter’s eight-step model:

      1.Establish a sense of urgency 2.Form a powerful guiding coalition 3.Create a vision 4.Communicate the vision 5.Empower others to act in the vision 6.Plan for and create short-term wins 7.Consolidate improvements and sustain the momentum for change 8.Institutionalize the new approaches

      Effective Change Implementation Top management support is cruciaal. Moeilijke veranderingen zoals restructuring and downsizing vragen om goede communicatie en innovation om moreel te behouden.

      Stress in the Context of Organizational Change Change uncertainty ontstaat door strategische, structurele of taakaspecten → kan worden verminderd door betrokkenheid. Verandering leidt soms tot job insecurity → emotionele uitputting. Oplossing: goede planning, copingstrategieën, leiderschap.

      Bronnen van steun (Figuur 15.2): Supervisor – benaderbaarheid Coworkers – begrip en groepsgevoel Organization – communicatie, hulpdiensten Partner, family, friends – emotionele steun

      Organizational stress = psychologische belasting (veel eisen, weinig controle). Gevolgen: burnout, exhaustion, detachment, gevoel van falen.

      Stressors veroorzaken drie soorten strain: Fysiologisch Psychologisch Gedragsmatig

      Kan leiden tot fight-or-flight response.

      Yerkes-Dodson law: stress kan prestaties verbeteren tot een bepaald niveau, daarna verslechteren ze.

      Challenge-related stress (eustress) = positief Hindrance-related stress = negatief → lager welzijn, hogere turnover

      Work-life balance: Crossover stress effect – stress meenemen naar huis Family-to-work conflict – gezinsproblemen beïnvloeden werk Work-school conflict – schoolprestaties lijden onder werk

      Social support is belangrijk. Het helpt bij zelfvertrouwen, controle en verbondenheid – ook wel het buffering effect genoemd. Vrouwen ervaren meer steun van vrouwelijke leidinggevenden; mannen krijgen steun ongeacht het geslacht van de leidinggevende.

      Sunday Scaries = stress voor de werkweek op zondag.

      Mindfulness-aanpak: de drie P’s Pause – neem een pauze, adem, reflecteer Perspective – stel jezelf vragen: “Ben ik oké?”, “Wat moet ik doen?” Prioritize – bepaal wat nú moet en wat later kan, gebruik takenlijstjes

      Succesvolle organizational change gebeurt wanneer de focus verschuift van managing change (van bovenaf opgelegd) naar leading change (inspireren op elk niveau).

      Een cruciale factor is compassionate leadership: Gedefinieerd als “ethisch-gebaseerde acties van leiders die anderen versterken, betrekken en in staat stellen hun beste zelf te worden, waardoor ze waarde creëren, klanten goed bedienen en de maatschappij ten goede komen”.

      Role conflict – Tegenstrijdige verwachtingen 1. Intersender role conflict 🔹 Wat is het? Twee of meer mensen (de "senders") geven tegenstrijdige opdrachten of verwachtingen aan dezelfde persoon. 2. Person-role conflict 🔹 Wat is het? Er is een conflict tussen de verwachtingen van de rol en je persoonlijke normen, waarden of overtuigingen 3. Interrole conflict 🔹 Wat is het? Verschillende rollen die je tegelijkertijd vervult, botsen met elkaar.

      🔹 Voorbeeld: Je bent zowel een ouder als een werknemer. Je moet op hetzelfde moment een belangrijk werkrapport afronden en je kind van school halen. Beide rollen eisen je aandacht, maar je kunt ze niet tegelijk uitvoeren.