Engineering stable and efficient ketol-acid reductoisomerases for industrial biotransformations using ancestral sequence reconstruction.

Engineering stable and efficient ketol-acid reductoisomerases for industrial biotransformations using ancestral sequence reconstruction. | 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 Engineering stable and efficient ketol-acid reductoisomerases for industrial biotransformations using ancestral sequence reconstruction. Gerhard Schenk, Oscar Paredes Trujillo, Gabriel Foley, Sebastian Porras, and 14 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8177142/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 Highly stable and efficient biocatalysts are required to commercialize sustainable enzymatic pathways for food, biofuel and biomaterial production. However, many routes for tailoring proteins to suit such applications remain time-consuming and achieve low throughput. Ancestral sequence reconstruction (ASR) is an effective approach for biocatalyst design as it leverages the natural trajectories of evolution to infer sequences with desirable enzymatic properties. Here, ASR was applied to systematically map the catalytic landscape of the NAD(P)H-dependent ketol-acid reductoisomerase (KARI) superfamily which catalyse the rate-limiting step in the conversion of glucose, a renewable feedstock, to the important platform chemical, isobutanol. We resurrect eight ancestral variants representing the diverse functional profiles of extant KARIs, demonstrating substantially improved catalytic efficiencies (up to 25-fold), isobutanol tolerance, and longevity (total turnover numbers >10 6 ), with melting temperatures reaching almost 100 °C (40 °C > benchmark KARIs). Together, this work contributes enhanced, potentially economically viable biocatalysts for sustainable manufacturing at industrial scale. Biological sciences/Biochemistry/Biocatalysis Biological sciences/Evolution/Molecular evolution Physical sciences/Chemistry/Green chemistry Biological sciences/Biotechnology/Molecular engineering Biological sciences/Chemical biology/Enzymes Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SchenkSupplementaryTableS1.xlsx Data Table in the Supplementary section SchenkSupportingInformation.pdf Engineering stable and efficient ketol-acid reductoisomerases for industrial biotransformations using ancestral sequence reconstruction 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. 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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-8177142","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":548972931,"identity":"293e5bd3-d704-49fa-aaaf-3ed8415a48de","order_by":0,"name":"Gerhard 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However, many routes for tailoring proteins to suit such applications remain time-consuming and achieve low throughput. Ancestral sequence reconstruction (ASR) is an effective approach for biocatalyst design as it leverages the natural trajectories of evolution to infer sequences with desirable enzymatic properties. Here, ASR was applied to systematically map the catalytic landscape of the NAD(P)H-dependent ketol-acid reductoisomerase (KARI) superfamily which catalyse the rate-limiting step in the conversion of glucose, a renewable feedstock, to the important platform chemical, isobutanol. We resurrect eight ancestral variants representing the diverse functional profiles of extant KARIs, demonstrating substantially improved catalytic efficiencies (up to 25-fold), isobutanol tolerance, and longevity (total turnover numbers \u003e10\u003csup\u003e6\u003c/sup\u003e), with melting temperatures reaching almost 100 °C (40 °C \u003e benchmark KARIs). 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