BCG vaccination reduces the rate of Mycobacterium tuberculosis dissemination between murine lungs

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This preprint studied how BCG vaccination affects within-host Mycobacterium tuberculosis (Mtb) dynamics and dissemination in murine lungs, using data from over 1,000 mice infected with an ultra-low dose. The authors built mathematical models that allowed both direct lung-to-lung and indirect lung–intermediate tissue–lung spread, which could fit unvaccinated data equally well under multiple plausible dissemination routes, and predicted rapid early replication, transient control over 1–2 months, and continued chronic growth. When the models were fit to BCG-vaccinated animals, the estimated inter-lung dissemination rate decreased by 89%, with only a modest 9% reduction in lung Mtb replication; stochastic simulations further showed that growth-reducing effects reduced numbers of infected mice, CFU levels, and bilateral spread. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Abstract The BCG vaccine remains the only licensed defense against tuberculosis (TB), yet its protective mechanisms are poorly understood. Utilizing data from a study of over 1,000 mice infected with an ultra-low dose (ULD) of Mycobacterium tuberculosis (Mtb), we developed mathematical models to quantify Mtb dynamics and dissemination in the murine lungs. Our models, incorporating both direct (lung-lung) and indirect dissemination(lung-intermediate tissue-lung) pathways, fit data from unvaccinated mice equally well, suggesting multiple plausible routes of Mtb spread; the models predicted rapid early Mtb replication, transient control within 1–2 months, and continued growth in chronic infection. Crucially, fitting these models to the data from BCG-vaccinated animals revealed that the vaccine reduces the inter-lung dissemination rate by 89%, while only modestly reducing the Mtb replication rate in the lung by 9%. Stochastic simulations demonstrated that growth-reducing vaccines, even at moderate efficacy decrease the number of infected mice, CFU levels, and bilateral spread. Finally, we used these parameterized models to calculate the sample sizes required to detect vaccine efficacy regarding Mtb clearance or dissemination. This framework quantifies vaccine efficacy in ULD-infected mice and supports preclinical evaluation of next-generation TB vaccines.
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BCG vaccination reduces the rate of Mycobacterium tuberculosis dissemination between murine lungs | 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 BCG vaccination reduces the rate of Mycobacterium tuberculosis dissemination between murine lungs Dipanjan Chakraborty, Vitaly Ganusov This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9190820/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 The BCG vaccine remains the only licensed defense against tuberculosis (TB), yet its protective mechanisms are poorly understood. Utilizing data from a study of over 1,000 mice infected with an ultra-low dose (ULD) of Mycobacterium tuberculosis (Mtb), we developed mathematical models to quantify Mtb dynamics and dissemination in the murine lungs. Our models, incorporating both direct (lung-lung) and indirect dissemination(lung-intermediate tissue-lung) pathways, fit data from unvaccinated mice equally well, suggesting multiple plausible routes of Mtb spread; the models predicted rapid early Mtb replication, transient control within 1–2 months, and continued growth in chronic infection. Crucially, fitting these models to the data from BCG-vaccinated animals revealed that the vaccine reduces the inter-lung dissemination rate by 89%, while only modestly reducing the Mtb replication rate in the lung by 9%. Stochastic simulations demonstrated that growth-reducing vaccines, even at moderate efficacy decrease the number of infected mice, CFU levels, and bilateral spread. Finally, we used these parameterized models to calculate the sample sizes required to detect vaccine efficacy regarding Mtb clearance or dissemination. This framework quantifies vaccine efficacy in ULD-infected mice and supports preclinical evaluation of next-generation TB vaccines. Biological sciences/Immunology/Infectious diseases/Tuberculosis Biological sciences/Immunology/Vaccines Tuberculosis Mycobacterium tuberculosis mathematical model within-host dynamics BCG vaccine disseminated disease Full Text Additional Declarations There is NO Competing Interest. Supplementary Files ChakrabortyGanusovsupplementaryfiles.pdf BCG vaccination reduces the rate of Mycobacterium tuberculosis dissemination between murine lungs 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. 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