Using Computational Predictions to Engineer Rubisco Kinetics

Elevated temperatures, associated with climate change, have drastic impacts on photosynthesis, reducing plant size and growth in the long run. Ribulose-1,5-bisphosphate carboxylase/oxygenase, Rubisco for short, is an enzyme that catalyzes the addition of CO2 to ribulose 1,5-bisphosphate (RuBP). The products of this reaction are fed into the Calvin cycle for carbohydrate production. However, Rubisco is notoriously inefficient, as it is catalytically slow and struggles to differentiate between CO2 and O2. The enzyme is comprised of eight large (LSu) and eight small (SSu) subunits. Despite not contributing residues to the active site, SSus are known to influence kinetics. Maddie Ceminsky, a member of the Gunn Lab, utilized FoldX, a computational tool that calculates the free energy of protein folding (∆Gfold), to generate an energetic landscape of all possible mutations within both subunits of Rubisco. From the landscape, six outliers varying from extremely stabilizing to extremely destabilizing were chosen for experimental validation in a Rubisco SynBio expression system. Mutations were introduced via site-direct mutagenesis, E. coli cells transformed, and protein production induced. Cells were then lysed, and Rubisco purified from the lysate, using a His-Trap column to take advantage of a His-tag on the SSu C-terminus. Spectrophotometric assays were used to measure the carboxylation speed of Rubisco. The carboxylation speed of each mutant was compared with that of the unmodified Rubisco. Our results show that FoldX’s stability predictions correlated with carboxylation rates and that moving forward, the software can be utilized to design Rubisco variants with desired kinetic properties.

The past 10 weeks flew by faster than I thought it would and yet here I am, enriched by this experience. My research helped me gain valuable skills that will be useful in any lab I may pursue in the future. My work has shown me what it means to be a scientist, an experience I will cherish for as long as I know. However, and more importantly, my experience here at BTI helped me understand not only future career options but also personal goals as well. I was able to gain a better understanding of what graduate school entails and what that means for me as a rising sophomore. I am truly grateful to the Gunn Lab for teaching me what it means to be supported by your mentors and working alongside diverse perspectives and identities. I feel more confident getting into research and beyond excited for what the future may bring.