An iterative computational design approach to increase the thermal endurance of a mesophilic enzyme

Abstract

Background: Strategies for maximizing the microbial production of bio-based chemicals and fuels include eliminating branched points to streamline metabolic pathways. While this is often achieved by removing key enzymes, the introduction of nonnative enzymes can provide metabolic shortcuts, bypassing branched points to decrease the production of undesired side-products. Pyruvate decarboxylase (PDC) can provide such a shortcut in industrially promising thermophilic organisms; yet to date, this enzyme has not been found in any thermophilic organism. Incorporating nonnative enzymes into host organisms can be challenging in cases such as this, where the enzyme has evolved in a very different environment from that of the host. Results: In this study, we use computational protein design to engineer the Zymomonas mobilis PDC to resist thermal denaturation at the growth temperature of a thermophilic host. We generate thirteen PDC variants using the Rosetta protein design software. We measure thermal stability of the wild-type PDC and PDC variants using circular dichroism. We then measure and compare enzyme endurance for wild-type PDC with the PDC variants at an elevated temperature of 60 °C (thermal endurance) using differential interference contrast imaging. Conclusions: We find that increases in melting temperature (T m) do not directly correlate with increases in thermal endurance at 60 °C. We also do not find evidence that any individual mutation or design approach is the major contributor to the most thermostable PDC variant. Rather, remarkable cooperativity among sixteen thermostabilizing mutations is key to rationally designing a PDC with significantly enhanced thermal endurance. These results suggest a generalizable iterative computational protein design approach to improve thermal stability and endurance of target enzymes.