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

• DOI: 10.1007/s00216-014-8331-5
• Publication Date: 2014-12-01T11:21:36Z
• Authors: Michael Witting; Marianna Lucio; Dimitrios Tziotis; Brigitte Wägele; Karsten Suhre; Romé Voulhoux; Steve Garvis; Philippe Schmitt-...
• Keywords: 0303 health sciences; Fourier Analysis; Salmonella enterica; Mass Spectrometry; High-Throughput Screening Assays; Disease Models, Animal; 03 medical and health sciences; Glucose; Host-Pathogen Interactions; Pseudomonas aeruginosa; Salmonella Infections; Animals; Metabolomics; [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology; Pseudomonas Infections; Amino Acids; Caenorhabditis elegans

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.