CD40-Immunosome: A Systems Modeling Framework for CD40–TRAF6 Signaling and CRISPR Synergy

CD40-Immunosome: A Systems Modeling Framework for CD40–TRAF6 Signaling and CRISPR Synergy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article CD40-Immunosome: A Systems Modeling Framework for CD40–TRAF6 Signaling and CRISPR Synergy Yashwant Nama This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9021170/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: The CD40–TRAF6 signaling axis regulates dendritic cell activation through tightly controlled NF-κB dynamics. The signal amplitude and duration are governed by intracellular negative feedback mechanisms, particularly SOCS1-mediated attenuation. Understanding how structural clustering and genetic perturbations reshape these dynamics requires mechanistic modeling. Methods: We developed the CD40-Immunosome, an interactive systems immunology framework integrating a three-variable ordinary differential equation (ODE) model of TRAF6, NF-κB, and SOCS1 kinetics. The platform implements (i) null-model comparison without feedback, (ii) stochastic Monte Carlo robustness analysis under ±20% parameter perturbations, and (iii) quantitative synergy scoring using area-under the-curve (AUC) metrics. Results: The feedback-enabled model produced transient NF-κB activation, followed by rapid attenuation, whereas the null model exhibited sustained activation consistent with chronic inflammatory dynamics. Monte Carlo simulations (n = 50) confirmed robustness to parameter perturbation (mean peak NF-κB = 1.59 ± 0.27 SD). Simulated SOCS1 deletion increased the cumulative signaling output by ∼ 3.2-fold relative to that of wild-type cells. Furthermore, structural stability simulations prioritized TMEM256 as a candidate modulator under modeled conditions. Conclusion: CD40-Immunosome provides a reproducible computational framework for exploring feedback-regulated immune signaling dynamics. The platform serves as a hypothesis-generating framework to support the mechanistic exploration of receptor clustering, structural perturbations, and targeted immunotherapies. Systems Biology Immunology Computational Biology Bioinformatics CD40 signaling CRISPR synergy immunotherapy computational modeling dark proteome systems immunology Full Text Additional Declarations The authors declare no competing interests. Supplementary Files SupplementaryCD40.pdf Supplementary Material: Code and Data Availability Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9021170","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":600041549,"identity":"1187c8d3-02df-4935-a3c3-7becc048284c","order_by":0,"name":"Yashwant Nama","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYDADAzBZAcTMzA0kaDlwBqSFkRQtB9tAJAEt5uynEz8wttnZm0skP3v8cV5tNH87UMuPim04tVj25G6WYGxLTtw5I83c4OC247kzDjM2MPacuY3bPQdyNwC1MCcY3E4wkzi47VhuA1ALM2MbHi3n327+wdhWb29wO/2bxME5x3LnE9RyI3cb0JbDjBtu5wBtaajJ3UBYy9ttFgnnjiduuP+mTOLMsQO5G4FaDuL1y/nczTc+lFXbG5w5vk2ioqYud975wwcf/KjArQUMEtngzMNg8gB+9SDwB86qI6x4FIyCUTAKRhwAAHzEYxurZSi+AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0003-3443-4413","institution":"Independent Researcher, Jaipur, Rajasthan, India","correspondingAuthor":true,"prefix":"","firstName":"Yashwant","middleName":"","lastName":"Nama","suffix":""}],"badges":[],"createdAt":"2026-03-03 14:14:42","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":true,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":true},"doi":"10.21203/rs.3.rs-9021170/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9021170/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103893562,"identity":"ac0ab28e-feaf-45dd-80d5-032c1747f130","added_by":"auto","created_at":"2026-03-04 08:28:32","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1211651,"visible":true,"origin":"","legend":"","description":"","filename":"NamaYCD40ImmunosomeModeling2026.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9021170/v1_covered_a6234a14-8dda-4c55-9d24-381ee4fbf84a.pdf"},{"id":103893534,"identity":"bd7f78ab-97fe-4817-b1fd-965868c808df","added_by":"auto","created_at":"2026-03-04 08:28:21","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":116913,"visible":true,"origin":"","legend":"\u003cp\u003eSupplementary Material: Code and Data Availability\u003c/p\u003e","description":"","filename":"SupplementaryCD40.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9021170/v1/76c9e964e7ac15c8ac9c28ad.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eCD40-Immunosome: A Systems Modeling Framework for CD40–TRAF6 Signaling and CRISPR Synergy\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Independent Researcher Jaipur, Rajasthan, India","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"CD40 signaling, CRISPR synergy, immunotherapy, computational modeling, dark proteome, systems immunology","lastPublishedDoi":"10.21203/rs.3.rs-9021170/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9021170/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The CD40–TRAF6 signaling axis regulates dendritic cell activation through tightly controlled NF-κB dynamics. The signal amplitude and duration are governed by intracellular negative feedback mechanisms, particularly SOCS1-mediated attenuation. Understanding how structural clustering and genetic perturbations reshape these dynamics requires mechanistic modeling.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eWe developed the CD40-Immunosome, an interactive systems immunology framework integrating a three-variable ordinary differential equation (ODE) model of TRAF6, NF-κB, and SOCS1 kinetics. The platform implements (i) null-model comparison without feedback, (ii) stochastic Monte Carlo robustness analysis under ±20% parameter perturbations, and (iii) quantitative synergy scoring using area-under the-curve (AUC) metrics.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The feedback-enabled model produced transient NF-κB activation, followed by rapid attenuation, whereas the null model exhibited sustained activation consistent with chronic inflammatory dynamics. Monte Carlo simulations (n = 50) confirmed robustness to parameter perturbation (mean peak NF-κB = 1.59 ± 0.27 SD). Simulated SOCS1 deletion increased the cumulative signaling output by ∼ 3.2-fold relative to that of wild-type cells. Furthermore, structural stability simulations prioritized TMEM256 as a candidate modulator under modeled conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eCD40-Immunosome provides a reproducible computational framework for exploring feedback-regulated immune signaling dynamics. 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