Noam Prywes

Engineering photosynthesis to improve carbon fixation

Research Summary

Plants, algae and cyanobacteria remove ~150 billion tonnes of carbon from the atmosphere every year. One enzyme, rubisco, is solely responsible for the carboxylation chemistry that ultimately feeds nearly all of the life on our planet. This enzyme has been extensively studied for decades but has proven very difficult to engineer.

In the Prywes lab we use new, high-throughput enzymology methods to map out the fitness landscape of rubisco in order to study its evolution and for engineering purposes. High-throughput DNA sequencing and machine learning are newly applicable to the study of this critical enzyme.

Photosynthetic engineering is an emerging discipline that has the potential to contribute to efforts to reduce carbon dioxide levels in our atmosphere. If rubisco could be improved it would have substantial implications for future efforts to draw down atmospheric carbon as fossil fuels are replaced by alternative energy sources.

Research Objectives

-Engineering photosynthesis by engineering a key bottleneck in the process of carbon fixation, the enzyme rubisco
-How can we design improved enzymes in the lab using laboratory evolution or machine learning?
-Can we learn about the mechanism of rubisco using high throughput data in combination with biophysical methods?
-Developing new methods to explore the functional landscapes of enzymes

Key Publications

Prywes N, Phillips NR, Oltrogge LM, Lindner S, Taylor-Kearney LJ, Tsai Y-CC, et al. A map of the rubisco biochemical landscape. Nature. 2025; 1–6.    

Prywes N, Phillips NR, Tuck OT, Valentin-Alvarado LE, Savage DF. Rubisco function, evolution, and engineering. Annu Rev Biochem. 2023;92: 385–410.    

Davidi D, Shamshoum M, Guo Z, Bar-On YM, Prywes N, Oz A, et al. Highly active rubiscos discovered by systematic interrogation of natural sequence diversity. EMBO J. 2020;39: e104081.    

Flamholz AI, Prywes N, Moran U, Davidi D, Bar-On YM, Oltrogge LM, et al. Revisiting Trade-offs between Rubisco Kinetic Parameters. Biochemistry. 2019;58: 3365–3376.