A map of the rubisco biochemical landscape

Noam Prywes; Naiya R Phillips; Luke M Oltrogge; Sebastian Lindner; Leah J Taylor-Kearney; Yi-Chin Candace Tsai; Benoit de Pins; Aidan E Cowan; Hana A Chang; Renée Z Wang; Laina N Hall; Daniel Bellieny-Rabelo; Hunter M Nisonoff; Rachel F Weissman; Avi I Flamholz; David Ding; Abhishek Y Bhatt; Oliver Mueller-Cajar; Patrick M Shih; Ron Milo; David F Savage

doi:10.1038/s41586-024-08455-0

A map of the rubisco biochemical landscape

Nature. 2025 Jan 22. doi: 10.1038/s41586-024-08455-0. Online ahead of print.

Authors

Noam Prywes^{1

2}, Naiya R Phillips³, Luke M Oltrogge^{2

3}, Sebastian Lindner⁴, Leah J Taylor-Kearney⁵, Yi-Chin Candace Tsai⁶, Benoit de Pins⁷, Aidan E Cowan^{3

8}, Hana A Chang⁷, Renée Z Wang⁵, Laina N Hall⁹, Daniel Bellieny-Rabelo^{1

10}, Hunter M Nisonoff¹¹, Rachel F Weissman³, Avi I Flamholz¹², David Ding^{1

2}, Abhishek Y Bhatt^{3

13}, Oliver Mueller-Cajar⁶, Patrick M Shih^{1

5

14

15}, Ron Milo⁷, David F Savage^{16

17

18}

Affiliations

¹ Innovative Genomics Institute, University of California Berkeley, Berkeley, CA, USA.
² Howard Hughes Medical Institute, University of California Berkeley, Berkeley, CA, USA.
³ Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA, USA.
⁴ University of Heidelberg, Heidelberg, Germany.
⁵ Department of Plant and Microbial Biology, University of California Berkeley, Berkeley, CA, USA.
⁶ School of Biological Sciences, Nanyang Technological University, Singapore, Singapore.
⁷ Department of Biology, University of Naples Federico II, Naples, Italy.
⁸ Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, USA.
⁹ Biophysics, University of California Berkeley, Berkeley, CA, USA.
¹⁰ California Institute for Quantitative Biosciences (QB3), University of California Berkeley, Berkeley, CA, USA.
¹¹ Center for Computational Biology, University of California Berkeley, Berkeley, CA, USA.
¹² Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
¹³ School of Medicine, University of California San Diego, La Jolla, CA, USA.
¹⁴ Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.
¹⁵ Feedstocks Division, Joint BioEnergy Institute, Emeryville, CA, USA.
¹⁶ Innovative Genomics Institute, University of California Berkeley, Berkeley, CA, USA. savage@berkeley.edu.
¹⁷ Howard Hughes Medical Institute, University of California Berkeley, Berkeley, CA, USA. savage@berkeley.edu.
¹⁸ Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA, USA. savage@berkeley.edu.

PMID: 39843747
DOI: 10.1038/s41586-024-08455-0

Abstract

Rubisco is the primary CO₂-fixing enzyme of the biosphere¹, yet it has slow kinetics². The roles of evolution and chemical mechanism in constraining its biochemical function remain debated^3,4. Engineering efforts aimed at adjusting the biochemical parameters of rubisco have largely failed⁵, although recent results indicate that the functional potential of rubisco has a wider scope than previously known⁶. Here we developed a massively parallel assay, using an engineered Escherichia coli⁷ in which enzyme activity is coupled to growth, to systematically map the sequence-function landscape of rubisco. Composite assay of more than 99% of single-amino acid mutants versus CO₂ concentration enabled inference of enzyme velocity and apparent CO₂ affinity parameters for thousands of substitutions. This approach identified many highly conserved positions that tolerate mutation and rare mutations that improve CO₂ affinity. These data indicate that non-trivial biochemical changes are readily accessible and that the functional distance between rubiscos from diverse organisms can be traversed, laying the groundwork for further enzyme engineering efforts.