In-Depth Computational Analysis of Natural and Artificial Carbon Fixation Pathways

Abstract

In the recent years, engineering new-to-nature CO2 and C1 fixing metabolic pathways made a leap forward. These new, artificial pathways promise higher yields and activity than natural ones like the Calvin-Benson-Bassham cycle. The question remains how to best predict their in vivo performance and what actually makes one pathway “better” than another. In this context, we explore aerobic carbon fixation pathways by a computational approach and compare them based on their ATP-efficiency and specific activity considering the kinetics and thermodynamics of the reactions. Beside natural pathways, this included the artificial Reductive Glycine Pathway, the CETCH cycle and two completely new cycles with superior stoichiometry: The Reductive Citramalyl-CoA cycle and the 2-Hydroxyglutarate-Reverse Tricarboxylic Acid cycle. A comprehensive kinetic data set was collected for all enzymes of all pathways and missing kinetic data was sampled with the Parameter Balancing algorithm. Kinetic and thermodynamic data were fed to the Enzyme Cost Minimization algorithm to check for respective inconsistencies and calculate pathway specific activities. We found that the Reductive Glycine Pathway, the CETCH cycle and the new Reductive Citramalyl-CoA cycle were predicted to have higher ATP-efficiencies and specific activities than the natural cycles. The Calvin Cycle performed better than previously thought, however. It can be concluded that the weaker overall characteristics in the design of the Calvin Cycle might be compensated by other benefits like robustness, low nutrient demand and a good compatibility with the host’s physiological requirements. Nevertheless, the artificial carbon fixation cycles hold great potential for future applications in Industrial Biotechnology and Synthetic Biology.