CaltechAUTHORS
Published May 28, 2024 | Version in press
Journal Article Open

A systematic exploration of bacterial form I rubisco maximal carboxylation rates

Creators

Abstract

Autotrophy is the basis for complex life on Earth. Central to this process is rubisco—the enzyme that catalyzes almost all carbon fixation on the planet. Yet, with only a small fraction of rubisco diversity kinetically characterized so far, the underlying biological factors driving the evolution of fast rubiscos in nature remain unclear. We conducted a high-throughput kinetic characterization of over 100 bacterial form I rubiscos, the most ubiquitous group of rubisco sequences in nature, to uncover the determinants of rubisco’s carboxylation velocity. We show that the presence of a carboxysome CO2 concentrating mechanism correlates with faster rubiscos with a median fivefold higher rate. In contrast to prior studies, we find that rubiscos originating from α-cyanobacteria exhibit the highest carboxylation rates among form I enzymes (≈10 s−1 median versus <7 s−1 in other groups). Our study systematically reveals biological and environmental properties associated with kinetic variation across rubiscos from nature.

Copyright and License

© 2024 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the data associated with this article, unless otherwise stated in a credit line to the data, but does not extend to the graphical or creative elements of illustrations, charts, or figures. This waiver removes legal barriers to the re-use and mining of research data. According to standard scholarly practice, it is recommended to provide appropriate citation and attribution whenever technically possible.

Acknowledgement

The authors thank Yoav Peleg, Ron Sender, Noam Prywes, Brian Ross, Dina Listov, Ralf Steuer, Avi Flamholz and David Savage for important conversations and productive feedback on this manuscript. The authors thank Michelle Gehring for additional information about unpublished data from their laboratory. This research was supported by the Mary and Tom Beck Canadian Center for Alternative Energy Research, Miel de Botton, the Schwartz Reisman Collaborative Science Program, and the Charles and Louise Gartner Professorial Chair.

Contributions

Benoit de Pins: Conceptualization; Data curation; Investigation; Methodology; Writing—original draft; Writing—review and editing. Lior Greenspoon: Investigation; Methodology. Yinon M Bar-On: Methodology. Melina Shamshoum: Methodology. Roee Ben-Nissan: Methodology. Eliya Milshtein: Methodology. Dan Davidi: Methodology. Itai Sharon: Data curation; Investigation. Oliver Mueller-Cajar: Conceptualization; Supervision; Writing—original draft; Writing—review and editing. Elad Noor: Conceptualization; Supervision; Methodology; Writing—original draft; Writing—review and editing. Ron Milo: Conceptualization; Supervision; Funding acquisition; Methodology; Writing—original draft; Project administration; Writing—review and editing.

Data Availability

All the data supporting the findings of this study as well as the 98 modeled protein structures, and the codes used for generating our list of rubiscos and for analyzing the results is open source and can be found in the following link: https://gitlab.com/milo-lab-public/rubisco-F1.
The source data of this paper are collected in the following database record: biostudies:S-SCDT-10_1038-S44318-024-00119-z.
 
APPENDIX (PDF document, 4.38 MB)
DATASET EV1 (Excel 2007 spreadsheet, 10.75 KB)
DATASET EV2 (Excel 2007 spreadsheet, 46.80 KB)
DATASET EV3 (Excel 2007 spreadsheet, 86.94 KB)
EXPANDED VIEW FIGURES (PDF document, 547.46 KB)

Conflict of Interest

The authors declare no competing interests.

Files

de-pins-et-al-2024-a-systematic-exploration-of-bacterial-form-i-rubisco-maximal-carboxylation-rates.pdf

Files (7.0 MB)

Name Size
md5:bead9c79ed8b6d4a4f4cfeb7a8a40425
4.6 MB Preview Download
md5:75c9db71d6f98a087f314f2a41334153
11.0 kB Download
md5:9d17c7abf09a70764a038f73f8e00f81
47.9 kB Download
md5:fc3921519bd85b7d640edd05d27817f0
89.0 kB Download
md5:4bfb4b6c46fb4b22b10a77e32f457c19
560.6 kB Preview Download
md5:5608e2d4c826d6e8d50fef37da97861a
1.7 MB Preview Download

Additional details

Funding

Mary and Tom Beck Canadian Center for Alternative Energy Research
Charles and Louise Gartner Professorial Chair
Miel de Botton
Schwartz Reisman Collaborative Science Program