{"paper_id":"0ecb03f2-5020-41ab-8438-c8e4811f3eb9","body_text":"Advancing virulence factor prediction using protein language models | 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 Advancing virulence factor prediction using protein language models Yitong Liu, Xin Cao, Jiani Li, Tao Li, Juanjuan Li, Xiang Ma, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4664562/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 Bacterial infections have emerged as the second leading cause of death globally, with their virulence factors (VFs) playing a critical role. Accurate prediction of VFs serves not only to elucidate the mechanisms of bacterial pathogenicity, but also offers new avenues for treating bacterial diseases. Machine learning (ML) stands out as a powerful tool for swiftly and precisely identifying VFs. However, a persistent challenge with existing ML methods is the use of outdated embedding techniques and a lack of differentiation between VFs of Gram-positive and Gram-negative bacteria. Results In this study, we introduced pLM4VF, a predictive framework that utilized ESM protein language models to extract VF characteristics of G+ and G- bacteriaseparately, and further integrated the models using the stacking strategy. The top-performing ensemble models, constructed using ESM pLMs, for both types of bacteria collectively constituted pLM4VF. Extensive benchmarking experiments on the independent test demonstrated that pLM4VF outperformed state-of-the-art methods. Biological validations through cytotoxicity and acute toxicity assays further corroborated the reliability of pLM4VF. An online tool (http://139.9.105.117:8081/) has been developed that enables inexperienced researchers on ML to obtain VFs of various bacteria at the whole-genome scale. Conclusion We believe that pLM4VF will offer substantial support in uncovering pathogenic mechanisms, developing novel antibacterial treatments and vaccines, thereby aiding in the prevention and management of bacterial diseases. Bacterial infection Virulence factor Protein language model Machine learning Stacking strategy Full Text Additional Declarations Competing interest reported. The authors declare no competing interests. Supplementary Files SupplementaryData.pdf 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-4664562\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":331583308,\"identity\":\"fe907199-31bc-4910-a0be-0d55beca3b9d\",\"order_by\":0,\"name\":\"Yitong Liu\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Hainan University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Yitong\",\"middleName\":\"\",\"lastName\":\"Liu\",\"suffix\":\"\"},{\"id\":331583309,\"identity\":\"e83e2500-3309-4e6c-b55f-ddb72c191f58\",\"order_by\":1,\"name\":\"Xin 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The authors declare no competing interests.\",\"formattedTitle\":\"Advancing virulence factor prediction using protein language models\",\"fulltext\":[],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":false,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":false,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":true,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":true,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"Bacterial infection, Virulence factor, Protein language model, Machine learning, Stacking strategy\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-4664562/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-4664562/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003e\\u003cstrong\\u003eBackground\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eBacterial infections have emerged as the second leading cause of death globally, with their virulence factors (VFs) playing a critical role. 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