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Real-time metabolome profiling of the metabolic switch between starvation and growth

Nature Methods volume 12, pages 1091–1097 (2015)Cite this article

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Abstract

Metabolic systems are often the first networks to respond to environmental changes, and the ability to monitor metabolite dynamics is key for understanding these cellular responses. Because monitoring metabolome changes is experimentally tedious and demanding, dynamic data on time scales from seconds to hours are scarce. Here we describe real-time metabolome profiling by direct injection of living bacteria, yeast or mammalian cells into a high-resolution mass spectrometer, which enables automated monitoring of about 300 compounds in 15–30-s cycles over several hours. We observed accumulation of energetically costly biomass metabolites in Escherichia coli in carbon starvation–induced stationary phase, as well as the rapid use of these metabolites upon growth resumption. By combining real-time metabolome profiling with modeling and inhibitor experiments, we obtained evidence for switch-like feedback inhibition in amino acid biosynthesis and for control of substrate availability through the preferential use of the metabolically cheaper one-step salvaging pathway over costly ten-step de novo purine biosynthesis during growth resumption.

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Figure 1: System for real-time metabolome profiling.
Figure 2: Metabolic shift in E. coli from starvation to growth.
Figure 3: Opposing dynamics of amino acids.
Figure 4: Metabolic response in purine nucleotide metabolism.

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Acknowledgements

We thank T. Hwa, M. Basan and M. Zampieri for discussions and D. Karst and M. Morbidelli (Institute of Chemical and Bioengineering, ETH Zurich, Zurich, Switzerland) for providing hybridoma cell cultures.

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Author notes

  1. Hannes Link

    Present address: Present address: Max Planck Institute for Terrestrial Microbiology, Marburg, Germany.,

Authors and Affiliations

  1. Institute of Molecular Systems Biology, Eidgenössische Technische Hochschule (ETH) Zurich, Zurich, Switzerland

    Hannes Link, Tobias Fuhrer, Luca Gerosa, Nicola Zamboni & Uwe Sauer

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  1. Tobias Fuhrer
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Contributions

H.L., T.F., L.G., N.Z. and U.S. designed the project, analyzed results and wrote the manuscript. H.L. and T.F. performed experiments. H.L. performed simulations.

Corresponding author

Correspondence to Uwe Sauer.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Real-time metabolome profiling of Saccharomyces cerevisiae.

Shown are fold change of ions annotated to citrate, succinate, AMP, reduced glutathione and lactate. Lines are the mean from 3 biological replicates and colored areas indicate standard deviation. A moving average filter was applied to raw data. Oxygen was removed at t = 10 min by flushing cultures with nitrogen.

Supplementary Figure 2 Growth resumption of E. coli.

Optical density at 600 nm of 2 hour carbon starved E. coli. Glucose was added at t = 0 min to a final concentration of 0.6 g l-1.

Supplementary Figure 3 Global dynamics during starvation and growth resumption.

K-means clustering of z-score normalized time profiles of 302 ions. The data set was clustered into a total of k = 10 clusters. Cluster centers are shown as red dots for the starvation phase (0 - 123 min) and blue dots for the glucose phase (123 - 150 min). Black dots represent individual profiles in the cluster. The number of ions in each cluster is indicated above each plot. Clusters are grouped according to the trends in the starvation and glucose phase as shown above each group. Ionization artifacts are caused by glucose ion suppression (cluster 9) and incomplete clearing of the electrospray chamber when injecting every 15 seconds (cluster 6). Time axis is different for the starvation and glucose phase.

Supplementary Figure 4 Amino acid dynamics during starvation and growth resumption.

Intensity of ions annotated to amino acids. Red: starvation; Blue: glucose phase. The exact mz is given in the upper right corner of each graph. Time axis is different for the starvation and glucose phase.

Supplementary Figure 5 Amino acid–degradation pathways in E. coli.

Pathways are adopted from the EcoCyc Database. Class 1 amino acids have decreased or constant concentrations during starvation. Class 2 amino acids accumulate during starvation (see Supplementary Fig. 4).

Supplementary Figure 6 Absolute concentrations of amino acids obtained by LC-MS.

Cells starved for 123 minutes before glucose was added. Black: samples of the whole cell broth. Magenta: samples of the supernatant. Note that scale of the time axis is different for the starvation and glucose phase.

Supplementary Figure 7 Amino acid dynamics during 23 h of starvation.

(a) Absolute concentrations of amino acids in the whole cell broth during 23 hours starvation measured by LCMS. Lines indicate linear regression for the first data points and numbers the slope in µmol/gDW/h. (b) Rate of accumulation obtained from linear regression is plotted against the according amino acid content in proteins (see Supplementary Table 6). The slope of the linear regression represents the net rate of protein degradation.

Supplementary Figure 8 Response of amino acids to chloramphenicol during exit from starvation.

Magenta: Intensity of ions annotated to the indicated amino acids obtained with the real-time system. 50 µM chloramphenicol was added at t = 135 min, dots are ion intensities and lines a moving average filter. Grey: Response during the glucose phase as shown in Supplementary Figure 4.

Supplementary Figure 9 Flux profiling of chloramphenicol-treated cells.

Fraction of unlabeled amino acids in exponentially growing E. coli washed for 30, 60 and 90 sec with U-13C glucose (black). Fraction of unlabeled amino acids in E. coli that were treated for 5 min with chloramphenicol before washing with U-13C glucose and chloramphenicol (red).

Supplementary Figure 10 Simulation results of the purine nucleotide model.

Simulation results of starvation (-5 min - 123 min) and growth resumption at 123 min obtained with the model of purine nucleotide metabolism (lines). Dots are scaled real-time data of xanthine, AMP and ATP.

Supplementary Figure 11 Growth resumption of E. coli cultures after 22 h of glucose starvation.

After 22 hours cells were centrifuged and resuspended in: old starvation medium (black), fresh M9 medium (blue) or fresh M9 medium supplemented with 20 μM isoleucine, leucine, valine, hypoxanthine and xanthine (red). The indicated carbon source was added at t = 0 min and optical density was monitored in 96-well flat transparent plates in a plate reader. Shown are three replicates (thin lines) and the average (bold lines).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–11 and Supplementary Notes 1 and 2 (PDF 3737 kb)

Supplementary Table 1

Functional categories used for pathway enrichment. Assignment was based on the metabolic model iJO1366 (Ref. 16) (XLSX 19 kb)

Supplementary Table 2

Properties of amino acids and ions annotated to amino acids (XLSX 11 kb)

Supplementary Software 1

Matlab serial port interface control scripts (ZIP 20 kb)

Supplementary Software 2

Matlab kinetic model scripts (ZIP 24 kb)

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Link, H., Fuhrer, T., Gerosa, L. et al. Real-time metabolome profiling of the metabolic switch between starvation and growth. Nat Methods 12, 1091–1097 (2015). https://doi.org/10.1038/nmeth.3584

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