ArchLips: A comprehensive in silico database for high-throughput identification of archaeal lipids using high-resolution mass spectrometry

ArchLips: A comprehensive in silico database for high-throughput identification of archaeal lipids using high-resolution mass spectrometry | 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 ArchLips: A comprehensive in silico database for high-throughput identification of archaeal lipids using high-resolution mass spectrometry Chuanlun Zhang, Fengfeng Zheng, Wenyong Yao, Wei He, Wan Zhang, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6774005/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Dec, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Archaeal membrane lipids are markedly distinct from those in bacteria and eukaryotes, serving as unique biomarkers for unraveling their ecological and biogeochemical roles. Recent advancements in high-resolution mass spectrometry-based lipidomic research have facilitated detailed cellular-level characterizations of lipid compounds. However, the lack of a comprehensive and dedicated database has severely limited large-scale, high-throughput investigations of archaeal lipids. We present ArchLips, a comprehensive database containing 218,868 in silico molecular structures and tandem mass spectra of 199,248 corresponding archaeal lipids. ArchLips enables the automatic and accurate annotation of archaeal lipid compounds characterized by high-resolution mass spectrometry from both pure cultures and environmental samples, serving as a transformative tool for enhancing our understanding of archaeal diversity and their ecological and evolutionary significance within global ecosystems. Earth and environmental sciences/Biogeochemistry Biological sciences/Biochemistry/Lipidomics Archaeal lipidomics mass spectrometry database biogeochemistry archaeal ecology Full Text Additional Declarations There is NO Competing Interest. Supplementary Files ArchLipsdatabaseSupplementaryinformation.pdf Supplementary Figures and Tables Cite Share Download PDF Status: Published Journal Publication published 15 Dec, 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-6774005","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":479211535,"identity":"d0f889d3-e5a8-4df5-a0d5-2d017ea09622","order_by":0,"name":"Chuanlun 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