Phenotypic Approaches to T Cell Activation: A Comparative Mathematical Modeling Study

Phenotypic Approaches to T Cell Activation: A Comparative Mathematical Modeling Study | 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 Article Phenotypic Approaches to T Cell Activation: A Comparative Mathematical Modeling Study Yogesh Bali, Alan D. Rendall This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6596119/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted 13 You are reading this latest preprint version Abstract T cells use their T cell antigen receptors (TCRs) to recognize peptides presented by major histocompatibility complex molecules (pMHC). These peptides may be low-affinity self-peptides or high-affinity foreign peptides from pathogens. Despite recognizing a broad range of affinities, TCR strigger significant immune responses only to strongly binding foreign peptides. The mechanisms enabling TCRs to distinguish diverse antigens with high sensitivity remain a key focus of research. Our goal is to analyze mathematical models of T cell activation for their ability to replicate key experimental features like optimal response, specificity, sensitivity, and antigen discrimination. We analyzed nine models using mathematical and numerical methods to examine their solutions, responses, and parameter sensitivity. We found that in all models, except kinetic proofreading with negative feedback, solutions converged to a unique steady state. Most response functions defined by ligand concentration and dissociation time showed an optimum value, except for the Occupancy, KPR, and stabilizing activation chain models. Models like KPR with negative feedback, limited/sustained signaling, and incoherent feedforward loops effectively replicated the key features of specificity, sensitivity, and antigen discrimination. Our sensitivity analysis identified phosphorylation rate as a key parameter influencing most model outcomes. This study highlights the strengths and limitations of current T-cell activation models, suggesting improvements to enhance their predictive accuracy in future research. Biological sciences/Immunology Physical sciences/Mathematics and computing T cell activation kinetic proofreading phenotypic models mathematical analysis sensitivity analysis Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryMaterial3.pdf Cite Share Download PDF Status: Published Journal Publication published 20 Dec, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 17 Nov, 2025 Reviews received at journal 16 Nov, 2025 Reviewers agreed at journal 01 Nov, 2025 Reviewers agreed at journal 01 Nov, 2025 Reviewers agreed at journal 20 Oct, 2025 Reviews received at journal 07 Jun, 2025 Reviewers agreed at journal 27 May, 2025 Reviewers agreed at journal 27 May, 2025 Reviewers invited by journal 27 May, 2025 Editor assigned by journal 27 May, 2025 Editor invited by journal 21 May, 2025 Submission checks completed at journal 21 May, 2025 First submitted to journal 05 May, 2025 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. 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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-6596119","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":462685128,"identity":"0a87aa26-e9d1-4295-a49e-c77e4ac194d9","order_by":0,"name":"Yogesh Bali","email":"","orcid":"","institution":"Johannes Gutenberg University Mainz","correspondingAuthor":false,"prefix":"","firstName":"Yogesh","middleName":"","lastName":"Bali","suffix":""},{"id":462685129,"identity":"9d97f60d-c0e1-4694-9d68-4ca2c6ccb016","order_by":1,"name":"Alan D. 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These peptides may be low-affinity self-peptides or high-affinity foreign peptides from pathogens. Despite recognizing a broad range of affinities, TCR strigger significant immune responses only to strongly binding foreign peptides. The mechanisms enabling TCRs to distinguish diverse antigens with high sensitivity remain a key focus of research.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur goal is to analyze mathematical models of T cell activation for their ability to replicate key experimental features like optimal response, specificity, sensitivity, and antigen discrimination. We analyzed nine models using mathematical and numerical methods to examine their solutions, responses, and parameter sensitivity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe found that in all models, except kinetic proofreading with negative feedback, solutions converged to a unique steady state. 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