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Untargeted metabolomics links glutathione to bacterial cell cycle progression

Nature Metabolism volume 2, pages 153–166 (2020)Cite this article

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Abstract

Cell cycle progression requires the coordination of cell growth, chromosome replication and division. Consequently, a functional cell cycle must be coupled with metabolism. However, direct measurements of metabolome dynamics remained scarce, in particular in bacteria. Here, we describe an untargeted metabolomics approach with synchronized Caulobacter crescentus cells to monitor the relative abundance changes of ~400 putative metabolites as a function of the cell cycle. While the majority of metabolite pools remain homeostatic, ~14% respond to cell cycle progression. In particular, sulfur metabolism is redirected during the G1–S transition, and glutathione levels periodically change over the cell cycle, with a peak in late S phase. A lack of glutathione perturbs cell size by uncoupling cell growth and division through dysregulation of KefB, a K+/H+ antiporter. Overall, we here describe the effects of the C. crescentus cell cycle progression on metabolism, and in turn relate glutathione and potassium homeostasis to timely cell division.

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Fig. 1: Untargeted dynamic metabolomics to monitor cell cycle progression.
Fig. 2: Global metabolic response to cell cycle progression.
Fig. 3: Cell cycle dependency of sulfur metabolism and glutathione.
Fig. 4: Loss of glutathione decouples growth from cell cycle progression.
Fig. 5: Lack of glutathione leads to kefB-dependent cell division defects.

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Data availability

The metabolomics dataset generated during this study is available through a MetaboLights database entry (https://www.ebi.ac.uk/metabolights/) with the study identifier MTBLS1402. Other data that support the findings of this study are available from the corresponding authors upon request.

Code availability

The computer code for the described ‘pairfinder’ workflow is deposited at https://pypi.org/project/idms-pairfinder-2/.

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Acknowledgements

We thank P. Christen (ETH Zurich) for technical support with LC–MS, J. v. Gienanth and C. Marulli (ETH Zurich) for experimental assistance in the early stages of this project, and J. Bögli and S. Stefanova (FACS Core Facility, Biozentrum, University of Basel) for help with flow cytometry. This work was supported by the Swiss National Science Foundation (grant no. 31003A_173094) and ETH Zurich to J.A.V., and by the Swiss National Science Foundation (grant no. 166503 and no. 185372) and an ERC Advanced Research Grant (grant no. 322809) to U.J.

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  1. These authors contributed equally: Patrick Kiefer, Andreas Kaczmarczyk.

Authors and Affiliations

  1. ETH Zurich, Institute of Microbiology, Zurich, Switzerland

    Johannes Hartl, Patrick Kiefer, Maximilian Mittelviefhaus, Fabian Meyer & Julia A. Vorholt

  2. Biozentrum of the University of Basel, Basel, Switzerland

    Andreas Kaczmarczyk & Urs Jenal

  3. ETH Zurich, Laboratory of Inorganic Chemistry, Zurich, Switzerland

    Thomas Vonderach & Bodo Hattendorf

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Contributions

J.H. and J.A.V. conceived the project. J.H. synchronized cells. J.H. and F.M. prepared the metabolomics samples. J.H. performed LC–MS measurements. J.H. and P.K. developed the algorithm for metabolite detection and quantification and performed data analysis. A.K. and U.J. planned and performed genetic manipulations, growth experiments and FACS measurements. J.H., A.K. and M.M. performed microscopy and image analysis. T.V. and B.H. performed elemental analysis. J.H. and J.A.V. wrote the manuscript with input from all authors.

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Correspondence to Johannes Hartl or Julia A. Vorholt.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–24, Methods and References

Reporting Summary

Supplementary Data 1

Cell cycle-dependent abundance profiles of metabolite features detected by LC–MS (nLC-QEx).

Supplementary Data 2

Cell cycle-dependent abundance profiles of metabolite features detected by LC–MS (UPLC-LTQ).

Supplementary Data 3

Clustermap of all metabolite abundance profiles throughout one cell cycle.

Supplementary Data 4

MS/MS spectra used for metabolite annotation.

Supplementary Data 5

Whole-genome sequencing results.

Supplementary Tables 1–11

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Hartl, J., Kiefer, P., Kaczmarczyk, A. et al. Untargeted metabolomics links glutathione to bacterial cell cycle progression. Nat Metab 2, 153–166 (2020). https://doi.org/10.1038/s42255-019-0166-0

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