A formal analysis of Listeria monocytogenes cross-contamination dynamics in multi-species biofilms: the role of coexisting microbiota

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This study examined how Listeria monocytogenes transfers from polymicrobial, multi-species biofilms to cold-smoked salmon, using stochastic modeling and high-replicate contact experiments (25 successive contacts per biofilm; 20 replicates each) under conditions intended to mimic low L. monocytogenes levels found in food processing environments. Three multi-species biofilms formed with L. monocytogenes plus coexisting strains were analyzed by estimating transfer rates and fitting them to gamma, Weibull, and log-normal distributions, followed by Monte Carlo simulation and clustering of similar transfer-rate profiles; transfer dynamics were comparable across the three multi-species biofilms but differed in contamination profiles. When compared with transfer from a single-species L. monocytogenes biofilm, multi-species biofilms produced higher transfer rates and supported higher survival and growth in refrigerated smoked salmon. The paper is centrally about endometriosis and adenomyosis? This 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 The risk of listeriosis is primarily linked to ready-to-eat (RTE) foods contaminated, raising concern among food producers. Contamination usually occurs in food processing environments (FPE), where L. monocytogenes can coexist with other bacterial species in polymicrobial biofilms. However, the transfer of the bacterium to food has focused almost exclusively on single-species biofilms, and the role of coexisting microbiota is largely unknown. Therefore, this study addressed the transfer dynamics of L. monocytogenes from multi-species biofilms to cold-smoked salmon following a stochastic approach. Three multi-species biofilms (F96, F107, and F168) were formed by different bacterial consortia composed of L. monocytogenes and several strains with which it coexists in food processing plants, under conditions that reproduced the low levels of L. monocytogenes commonly found in them, thus mimicking real contamination events. Transfer was performed by 25 successive contacts of each biofilm with different salmon fillets, and a high number of replicates of each biofilm (20) were used in order to record the stochasticity of the process. Transfer rates (TR) were determined, fitted to well-known distributions (gamma, Weibull and log-normal), and then modelled using a Monte Carlo method. Similar dynamics were thus defined for all three biofilms. Next, TRs from each biofilm with non-significantly different values were grouped into clusters, and probability density functions were modelled for each cluster. This approach showed different contamination profiles among the biofilms. This same approach was applied to the transfer dynamics from a single-species biofilm (L96) of L. monocytogenes. Thus, it was observed that contamination from multi-species biofilms (F96) resulted in higher TRs than contamination from single-species biofilms (L96), revealing a major role of the coexisting microbiota. Additionally, L. monocytogenes showed higher survival and growth capacity in refrigerated smoked salmon when transferred from multi-species biofilms than from single-species biofilms, implying a significantly higher risk for food safety. Being polymicrobial biofilms overwhelmingly prevalent in FPEs, this research provides a basis for scenarios that should be incorporated into challenge studies, ultimately leading to more effective control by manufacturers.
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A formal analysis of Listeria monocytogenes cross-contamination dynamics in multi-species biofilms: the role of coexisting microbiota | 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 A formal analysis of Listeria monocytogenes cross-contamination dynamics in multi-species biofilms: the role of coexisting microbiota Raquel A. Nogueira, Juan J. Rodríguez-Herrera, José Luis López-Carmona, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6145067/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract The risk of listeriosis is primarily linked to ready-to-eat (RTE) foods contaminated, raising concern among food producers. Contamination usually occurs in food processing environments (FPE), where L. monocytogenes can coexist with other bacterial species in polymicrobial biofilms. However, the transfer of the bacterium to food has focused almost exclusively on single-species biofilms, and the role of coexisting microbiota is largely unknown. Therefore, this study addressed the transfer dynamics of L. monocytogenes from multi-species biofilms to cold-smoked salmon following a stochastic approach. Three multi-species biofilms (F96, F107, and F168) were formed by different bacterial consortia composed of L. monocytogenes and several strains with which it coexists in food processing plants, under conditions that reproduced the low levels of L. monocytogenes commonly found in them, thus mimicking real contamination events. Transfer was performed by 25 successive contacts of each biofilm with different salmon fillets, and a high number of replicates of each biofilm (20) were used in order to record the stochasticity of the process. Transfer rates (TR) were determined, fitted to well-known distributions (gamma, Weibull and log-normal), and then modelled using a Monte Carlo method. Similar dynamics were thus defined for all three biofilms. Next, TRs from each biofilm with non-significantly different values were grouped into clusters, and probability density functions were modelled for each cluster. This approach showed different contamination profiles among the biofilms. This same approach was applied to the transfer dynamics from a single-species biofilm (L96) of L. monocytogenes . Thus, it was observed that contamination from multi-species biofilms (F96) resulted in higher TRs than contamination from single-species biofilms (L96), revealing a major role of the coexisting microbiota. Additionally, L. monocytogenes showed higher survival and growth capacity in refrigerated smoked salmon when transferred from multi-species biofilms than from single-species biofilms, implying a significantly higher risk for food safety. Being polymicrobial biofilms overwhelmingly prevalent in FPEs, this research provides a basis for scenarios that should be incorporated into challenge studies, ultimately leading to more effective control by manufacturers. Biological sciences/Microbiology/Biofilms Biological sciences/Microbiology/Communities Biological sciences/Microbiology/Pathogens Full Text Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 02 May, 2025 Reviews received at journal 28 Apr, 2025 Reviews received at journal 27 Apr, 2025 Reviews received at journal 22 Apr, 2025 Reviewers agreed at journal 21 Apr, 2025 Reviewers agreed at journal 19 Apr, 2025 Reviewers agreed at journal 17 Apr, 2025 Reviewers agreed at journal 17 Apr, 2025 Reviewers invited by journal 16 Apr, 2025 Editor assigned by journal 27 Mar, 2025 Submission checks completed at journal 18 Mar, 2025 First submitted to journal 03 Mar, 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. 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-6145067","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":446955240,"identity":"9b63f977-8a8c-403a-a3cb-d566c7ba59ea","order_by":0,"name":"Raquel A. 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