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Metabolic flux analysis in leaf metabolism quantifies the link between photorespiration and one carbon metabolism

Nature Plants volume 11, pages 1877–1889 (2025)Cite this article

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Abstract

Photorespiration is the second largest carbon flux in most leaves and is integrated into metabolism broadly including one-carbon (C1) metabolism. Photorespiratory intermediates such as serine and others may serve as sources of C1 units, but it is unclear to what degree this happens in vivo, whether altered photorespiration changes flux to C1 metabolism, and if so through which intermediates. To clarify these questions, we quantified carbon flux from photorespiration to C1 metabolism using 13CO2 labelling and isotopically non-stationary metabolic flux analysis in Arabidopsis thaliana under different O2 concentrations which modulate photorespiration. The results revealed that ~5.8% of assimilated carbon passes to C1 metabolism under ambient photorespiratory conditions, but this flux greatly decreases under limited photorespiration. Furthermore, the primary carbon flux from photorespiration to C1 metabolism is through serine. Our results provide fundamental insight into how photorespiration is integrated into C1 metabolism, with possible implications for C1 metabolic response to climate change.

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Fig. 1: Schematic representation of the link between photorespiration and C1 metabolism.
Fig. 2: Net CO2 assimilation, rubisco carboxylation and oxygenation rate in response to different photorespiratory conditions.
Fig. 3: 13C labelling kinetics of photorespiratory intermediates and C1-containing metabolites in wild-type A. thaliana leaves exposed to 2% O2 and 21% O2.
Fig. 4: Photorespiratory and C1 metabolic fluxes in A. thaliana wild-type leaves exposed to 21% O2 and 2% O2 conditions.

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Data, code and models are available in the Supplementary Information.

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Acknowledgements

This work was supported by the National Science Foundation (award numbers 2015843 and MCB-2015828). Work in the laboratory of B.J.W. is supported by grant number DE-FG02-91ER20021 from the Division of Chemical Sciences, Geosciences and Biosciences, Office of Basic Energy Sciences of the US Department of Energy. We thank L. Chen, C. Johnny and A. Schilmiller (Michigan State University Mass Spectrometry and Metabolomics Core Facility) for excellent support of mass spectrometry analysis. We thank X. Fu (Michigan State University) for helpful discussions on INST-MFA. We thank S. E. Weise, T. D. Sharkey, Y. Xu and P. Srivastava for providing technical support in measuring starch and sucrose partitioning. We also thank L. Gregory for taking care of catalase knock plants during the experimental period.

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Authors and Affiliations

  1. Department of Energy Plant Research Laboratory, Michigan State University, East Lansing, MI, USA

    Kelem Gashu & Berkley J. Walker

  2. Department of Civil and Environmental Engineering, Grainger College of Engineering, University of Illinois Urbana-Champaign, Urbana, IL, USA

    Joshua A. M. Kaste

  3. Institute of Biological Chemistry, Washington State University, Pullman, WA, USA

    Sanja Roje

  4. Department of Plant Biology, Michigan State University, East Lansing, MI, USA

    Berkley J. Walker

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  1. Kelem Gashu
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  2. Joshua A. M. Kaste
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Contributions

B.J.W. and K.G. designed the experiments with input from S.R. Additional statistical analysis was performed by J.A.M.K. K.G. carried out mass spectrometry analysis and gas-exchange experiments. B.J.W. and K.G. developed the INST-MFA model for fitting against the data. All authors participated in writing. B.J.W. serves as the author responsible for contact and ensures communication.

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Correspondence to Berkley J. Walker.

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Nature Plants thanks Younès Dellero, Alisdair Fernie, Edward Smith and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–15 and Materials and Methods.

Reporting Summary

Supplementary Code 1

Python code for probability of superiority analysis.

Supplementary Model 1

INCA models and data for the 2% condition comprising .mat model files and a .m file for running the models on a computing cluster.

Supplementary Model 2

INCA models and data for the 21% condition comprising .mat model files and a .m file for running the models on a computing cluster.

Supplementary Data 1

Flux solutions, fractional enrichments and statistics comparing metabolomics results.

Supplementary Data 2

Model validation results.

Supplementary Data 3

Probability of superiority results.

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Gashu, K., Kaste, J.A.M., Roje, S. et al. Metabolic flux analysis in leaf metabolism quantifies the link between photorespiration and one carbon metabolism. Nat. Plants 11, 1877–1889 (2025). https://doi.org/10.1038/s41477-025-02091-w

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