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DI-ICR-FT-MS-based high-throughput deep metabotyping: a case study of the Caenorhabditis elegans–Pseudomonas aeruginosa infection model

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Abstract

In metabolomics there is an ever-growing need for faster and more comprehensive analysis methods to cope with the increasing size of biological studies. Direct-infusion ion-cyclotron-resonance Fourier-transform spectrometry (DI-ICR-FT-MS) is used in non-targeted metabolomics to obtain high-resolution snapshots of the metabolic state of a system. We applied this technology to a Caenorhabditis elegans–Pseudomonas aeruginosa infection model and optimized times needed for cultivation and mass-spectrometric analysis. Our results reveal that DI-ICR-FT-MS is a promising tool for high-throughput in-depth non-targeted metabolomics. We performed whole-worm metabolomics and recovered markers of the induced metabolic changes in C. elegans brought about by interaction with pathogens. In this investigation, we reveal complex metabolic phenotypes enabling clustering based upon challenge. Specifically, we observed a marked decrease in amino-acid metabolism with infection by P. aeruginosa and a marked increase in sugar metabolism with infection by Salmonella enterica. We were also able to discriminate between infection with a virulent wild-type Pseudomonas and with an attenuated mutant, making it possible to use this method in larger genetic screens to identify host and pathogen effectors affecting the metabolic phenotype of infection.

Total time needed for generation of a data matrix suitable for statistical analysis from cultivation took close to 4 days with several possible break points. Time needed for cultivation (excluding preparation of plates, etc.) was 3 days, whereas the extraction needed only 1 hour and finally mass spectrometry was performed in less than one day for positive and negative ionization mode

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Acknowledgments

The authors would like to thank Thomas Rattei for the excellent leadership of the Pathomics project and suggestions to pathogen–host metabolomics.

The study was funded by German Federal Ministry of Education and Research in the frame of the ERA-NET project “Pathogen-host metabolomics and interactomics (Pathomics)” (0315442C).

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Author notes

  1. Steve Garvis

    Present address: Laboratoire de Biologie Moléculaire de la Cellule UMR5239 CNRS/ENS Lyon/UCBL/HCL, Ecole normale supérieure de Lyon 46, Allée d’Italie, 69364, Lyon cedex 07, France

Authors and Affiliations

  1. Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany

    Michael Witting, Marianna Lucio, Dimitrios Tziotis & Philippe Schmitt-Kopplin

  2. Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstaedter Landstrasse 1, 85764, Neuherberg, Germany

    Brigitte Wägele

  3. Department of Physiology and Biophysics, Weill Cornell Medical College in Qatar, P.O. Box 24144, Education City–Qatar Foundation, Doha, Qatar

    Karsten Suhre

  4. Centre National de la Recherche Scientifique, 31 Chemin Joseph Aiguier, 13402, Marseille Cedex 20, France

    Romé Voulhoux & Steve Garvis

  5. Chair of Analytical Food Chemistry, Technische Universität München, Alte Akademie 10, 85354, Freising-Weihenstephan, Germany

    Philippe Schmitt-Kopplin

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  1. Michael Witting
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Correspondence to Michael Witting or Philippe Schmitt-Kopplin.

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Witting, M., Lucio, M., Tziotis, D. et al. DI-ICR-FT-MS-based high-throughput deep metabotyping: a case study of the Caenorhabditis elegans–Pseudomonas aeruginosa infection model. Anal Bioanal Chem 407, 1059–1073 (2015). https://doi.org/10.1007/s00216-014-8331-5

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