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

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.