Telling metabolic stories to explore metabolomics data: a case study on the yeast response to cadmium exposure
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2014Metadata
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Vieira Milreu, Paulo
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Telling metabolic stories to explore metabolomics data: a case study on the yeast response to cadmium exposure
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Abstract
Motivation: 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.
Availability and implementation: The code for the method
presented in this article is available at http://gobbolino.gforge.inria.fr.
General note
Artículo de publicación ISI
Patrocinador
European Research Council under the European
Community’s Seventh Framework Programme (FP7/2007-
2013)/ERC grant agreement no. (247073)10; the French project
(ANR MIRI BLAN08-1335497); and the ANR funded LabEx
ECOFECT. It was partially supported by the Plateforme
Bioinformatique de Toulouse, ANR-BBSRC Systryp, the
CIRIC-INRIA Chile line Natural Resources, the NWO-CLS
MEMESA project and the ‘DISCO’ PRIN National Research
Project.
Identifier
URI: https://repositorio.uchile.cl/handle/2250/126919
DOI: doi:10.1093/bioinformatics/btt597
Quote Item
Bioinformatics. 2014 Jan 1;30(1):61-70
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