Multicenter Evaluation of Label-Free Quantification in Human Plasma: Benchmarking with a High Dynamic Range Multispecies Sample Set

Multicenter Evaluation of Label-Free Quantification in Human Plasma: Benchmarking with a High Dynamic Range Multispecies Sample Set | 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 Multicenter Evaluation of Label-Free Quantification in Human Plasma: Benchmarking with a High Dynamic Range Multispecies Sample Set Ute Distler, Han Yoo, Oliver Kardell, Dana Hein, Malte Sielaff, and 33 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5618718/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Oct, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Human plasma is routinely collected during clinical care and constitutes a rich source of biomarkers for diagnostics and patient stratification. Liquid chromatography-mass spectrometry (LC-MS)-based proteomics is a key method for plasma biomarker discovery, but the high dynamic range of plasma proteins poses significant challenges for MS analysis and data processing. To benchmark the quantitative performance of neat plasma analysis, we generated a multispecies sample set based on a human tryptic plasma digest containing varying low level spike-ins of yeast and E. coli tryptic proteome digests, termed PYE. The sample set was distributed across twelve different sites and analysed on state-of-the-art LC-MS platforms in data-dependent (DDA) and data-independent acquisition (DIA) modes, resulting in a total of 1,116 individual LC-MS runs. Centralized data analysis showed that DIA methods outperform DDA-based approaches regarding identifications, data completeness, accuracy, and precision. DIA achieved excellent technical reproducibility, as demonstrated by coefficients of variation (CVs) between 1.5% and 4.6% at protein level. Comparative analysis of different setups clearly shows a high overlap in identified proteins and proves that accurate and precise quantitative measurements are feasible across multiple sites, even in a complex matrix such as plasma, using state-of-the-art instrumentation. The collected dataset, including the PYE sample set and strategy presented, serves as a valuable resource for optimizing the accuracy and reproducibility of LC-MS and bioinformatic workflows for clinical plasma proteome analysis. Biological sciences/Biological techniques/Proteomic analysis Biological sciences/Computational biology and bioinformatics/Proteome informatics Health sciences/Medical research/Translational research Biological sciences/Systems biology/Standardization Biological sciences/Biological techniques/Mass spectrometry Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SupplTable1.xlsx Supplementary Table 1 SupplTable2.xlsx Supplementary Table 2 SupplTable3.xlsx Supplementary Table 3 SupplTable4.xlsx Supplementary Table 4 SupplTable5.xlsx Supplementary Table 5 SupplTable6.xlsx Supplementary Table 6 00PYEmanuscriptSupplemetaryInfo.pdf Supplementary Info File Cite Share Download PDF Status: Published Journal Publication published 02 Oct, 2025 Read the published version in Nature Communications → 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. 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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-5618718","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":391896851,"identity":"a78860bb-926c-436d-a9a8-8006f92cfd8f","order_by":0,"name":"Ute 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Set","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5618718/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5618718/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Human plasma is routinely collected during clinical care and constitutes a rich source of biomarkers for diagnostics and patient stratification. Liquid chromatography-mass spectrometry (LC-MS)-based proteomics is a key method for plasma biomarker discovery, but the high dynamic range of plasma proteins poses significant challenges for MS analysis and data processing. To benchmark the quantitative performance of neat plasma analysis, we generated a multispecies sample set based on a human tryptic plasma digest containing varying low level spike-ins of yeast and E. coli tryptic proteome digests, termed PYE. The sample set was distributed across twelve different sites and analysed on state-of-the-art LC-MS platforms in data-dependent (DDA) and data-independent acquisition (DIA) modes, resulting in a total of 1,116 individual LC-MS runs. Centralized data analysis showed that DIA methods outperform DDA-based approaches regarding identifications, data completeness, accuracy, and precision. DIA achieved excellent technical reproducibility, as demonstrated by coefficients of variation (CVs) between 1.5% and 4.6% at protein level. Comparative analysis of different setups clearly shows a high overlap in identified proteins and proves that accurate and precise quantitative measurements are feasible across multiple sites, even in a complex matrix such as plasma, using state-of-the-art instrumentation. The collected dataset, including the PYE sample set and strategy presented, serves as a valuable resource for optimizing the accuracy and reproducibility of LC-MS and bioinformatic workflows for clinical plasma proteome analysis.","manuscriptTitle":"Multicenter Evaluation of Label-Free Quantification in Human Plasma: Benchmarking with a High Dynamic Range Multispecies Sample Set","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-19 02:12:36","doi":"10.21203/rs.3.rs-5618718/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"6f57fe57-0d58-47d2-a392-a89449d67b24","owner":[],"postedDate":"December 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":41773270,"name":"Biological sciences/Biological techniques/Proteomic analysis"},{"id":41773271,"name":"Biological sciences/Computational biology and bioinformatics/Proteome informatics"},{"id":41773272,"name":"Health sciences/Medical research/Translational research"},{"id":41773273,"name":"Biological sciences/Systems biology/Standardization"},{"id":41773274,"name":"Biological sciences/Biological techniques/Mass spectrometry"}],"tags":[],"updatedAt":"2025-10-03T07:06:59+00:00","versionOfRecord":{"articleIdentity":"rs-5618718","link":"https://doi.org/10.1038/s41467-025-64501-z","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-10-02 04:00:00","publishedOnDateReadable":"October 2nd, 2025"},"versionCreatedAt":"2024-12-19 02:12:36","video":"","vorDoi":"10.1038/s41467-025-64501-z","vorDoiUrl":"https://doi.org/10.1038/s41467-025-64501-z","workflowStages":[]},"version":"v1","identity":"rs-5618718","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5618718","identity":"rs-5618718","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}