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Metabolomics

, Volume 11, Issue 4, pp 908–919 | Cite as

Projected Orthogonalized CHemical Encounter MONitoring (POCHEMON) for microbial interactions in co-culture

  • Jeroen J. JansenEmail author
  • Lionel Blanchet
  • Lutgarde M. C. Buydens
  • Samuel Bertrand
  • Jean-Luc Wolfender
Original Article

Abstract

Micro-organismal interspecies competition induces highly complex ecological interactions. Its associated biochemistry is an extremely rich source for bioactive molecules, that can be evaluated by comparing assays of separated species to ‘co-cultures’ in which they compete. The untargeted view that metabolomics provides, gives unprecedented insight into the wealth of involved metabolites. Currently used multivariate data analysis methods in metabolomics, like principal component analysis, do not focus upon up- and down-regulation of constitutive metabolite pools during competition. This severely limits the interpretation of competition mechanisms and the associated metabolites from the extremely information-rich metabolomics data. Projected orthogonal chemical encounter monitoring (POCHEMON) is a novel multivariate data analysis method that reveals all competition-related biochemical changes from the co-cultures: both up- or down-regulated, and de novo synthesised metabolites. It describes the metabolite composition of a co-culture assay by a mixture of the metabolites expressed in both separated species. Aspects of the co-culture metabolism that cannot be described in this way, are present only in the co-cultures and therefore likely associated to interspecies competition. We highlight the potential of POCHEMON by a study on fungal interactions in onychomycosis, a nail infection that may severely affect immuno-suppressed individuals. The resulting model reveals many unexpected or as yet unknown metabolites involved in the competition, that can be specifically identified as up- or down-regulated or de novo produced upon competition.

Keywords

Chemometrics Co-culture Interspecies competition Metabolomics Multivariate data analysis 

Notes

Acknowledgments

This work was supported by the Swiss National Science Foundation Sinergia Grant CRSII3_127187 and Grant CR2313_143733, which were awarded to J.-L. W.; Michel Monod (Dermatology and Venereology Department, Laboratory of Mycology, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland) is acknowledged for providing the fungal strains and Katia Gindro and Olivier Schumpp (Swiss Federal Research Station Agroscope Changins-Wädenswil, Nyon, Switzerland) for the management of the co-culture experiments and for scientific advice.

Conflict of Interest

We have no conflict of interest to declare.

Compliance with ethical requirements

This article does not contain any studies with human or animal subjects.

Supplementary material

11306_2014_748_MOESM1_ESM.docx (677 kb)
Supplementary material 1 (DOCX 676 kb)

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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Jeroen J. Jansen
    • 1
    Email author
  • Lionel Blanchet
    • 1
    • 2
  • Lutgarde M. C. Buydens
    • 1
  • Samuel Bertrand
    • 3
    • 4
  • Jean-Luc Wolfender
    • 3
  1. 1.Institute for Molecules and MaterialsRadboud University NijmegenNijmegenThe Netherlands
  2. 2.Department of Biochemistry, Nijmegen Centre for Molecular Life SciencesRadboud University Medical CentreNijmegenThe Netherlands
  3. 3.School of Pharmaceutical SciencesUniversity of Geneva/University of LausanneGeneva 4Switzerland
  4. 4.Groupe Mer, Molécules, Santé-EA 2160, UFR des Sciences pharmaceutiques et biologiques, Université de NantesNantes Cedex 01France

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