title: Telling metabolic stories to explore metabolomics data: a case study on the yeast response to cadmium exposure.
abstract: BACKGROUND
  The increasing availability of metabolomics data enables to better understand the metabolic processes involved in the immediate response of an organism to environmental changes and stress. The data usually come in the form of a list of metabolites whose concentrations significantly changed under some conditions, and are thus not easy to interpret without being able to precisely visualize how such metabolites are interconnected.
  
  
  RESULTS
  We present a method that enables to organize the data from any metabolomics experiment into metabolic stories. Each story corresponds to a possible scenario explaining the flow of matter between the metabolites of interest. These scenarios may then be ranked in different ways depending on which interpretation one wishes to emphasize for the causal link between two affected metabolites: enzyme activation, enzyme inhibition or domino effect on the concentration changes of substrates and products. Equally probable stories under any selected ranking scheme can be further grouped into a single anthology that summarizes, in a unique subnetwork, all equivalently plausible alternative stories. An anthology is simply a union of such stories. We detail an application of the method to the response of yeast to cadmium exposure. We use this system as a proof of concept for our method, and we show that we are able to find a story that reproduces very well the current knowledge about the yeast response to cadmium. We further show that this response is mostly based on enzyme activation. We also provide a framework for exploring the alternative pathways or side effects this local response is expected to have in the rest of the network. We discuss several interpretations for the changes we see, and we suggest hypotheses that could in principle be experimentally tested. Noticeably, our method requires simple input data and could be used in a wide variety of applications.
  
  
  METHODS
  The code for the method presented in this article is available at http://gobbolino.gforge.inria.fr.
authors.affiliation: INRIA Grenoble Rhône-Alpes & Université de Lyon, F-69000 Lyon, Université Lyon 1; CNRS, UMR5558 LBBE, France, Laboratório Nacional de Computação Científica (LNCC), Petrópolis, Brazil, LISBP, UMR CNRS 5504 - INRA 792, Toulouse, France, Mathomics, Center for Mathematical Modeling (UMI-2807 CNRS) and Center for Genome Regulation (Fondap 15090007), University of Chile, Santiago, Chile Lab. Statistique et Génome, CNRS UMR8071 INRA1152, Université d'Évry, France, Scuola Normale Superiore, 56126 Pisa, Italy, Laboratoire d'Etude du Métabolisme des Médicaments, DSV/iBiTecS/SPI, CEA/Saclay, 91191 Gif-sur-Yvette, France, La Sapienza University of Rome, Rome, Dipartimento di Sistemi e Informatica, Università di Firenze, I-50134 Firenze, Italy, VU University and CWI, Amsterdam, The Netherlands and INRA UMR1331 - Toxalim, Toulouse, France.
authors.forename: Paulo Vieira
authors.initials: PV
authors.lastname: Milreu
authors.forename: Cecilia Coimbra
authors.initials: CC
authors.lastname: Klein
authors.forename: Ludovic
authors.initials: L
authors.lastname: Cottret
authors.forename: Vicente
authors.initials: V
authors.lastname: Acuña
authors.forename: Etienne
authors.initials: E
authors.lastname: Birmelé
authors.forename: Michele
authors.initials: M
authors.lastname: Borassi
authors.forename: Christophe
authors.initials: C
authors.lastname: Junot
authors.forename: Alberto
authors.initials: A
authors.lastname: Marchetti-Spaccamela
authors.forename: Andrea
authors.initials: A
authors.lastname: Marino
authors.forename: Leen
authors.initials: L
authors.lastname: Stougie
authors.forename: Fabien
authors.initials: F
authors.lastname: Jourdan
authors.forename: Pierluigi
authors.initials: P
authors.lastname: Crescenzi
authors.forename: Vincent
authors.initials: V
authors.lastname: Lacroix
authors.forename: Marie-France
authors.initials: MF
authors.lastname: Sagot
mesh_terms: D002104:Cadmium / Q000494:pharmacology*; D004789:Enzyme Activation; D005978:Glutathione / Q000096:biosynthesis; D055432:Metabolomics / Q000379:methods*; D012441:Saccharomyces cerevisiae / Q000187:drug effects* / Q000378:metabolism*
chemical_list: D002104:Cadmium; D005978:Glutathione