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Flux-dependent graphs for metabolic networks

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Title: Flux-dependent graphs for metabolic networks
Authors: Beguerisse, M
Bosque, G
Oyarzun, DA
Pico, J
Barahona, M
Item Type: Journal Article
Abstract: Cells adapt their metabolic fluxes in response to changes in the environment. We present a framework for the systematic construction of flux-based graphs derived from organism-wide metabolic networks. Our graphs encode the directionality of metabolic flows via edges that represent the flow of metabolites from source to target reactions. The methodology can be applied in the absence of a specific biological context by modelling fluxes probabilistically, or can be tailored to different environmental conditions by incorporating flux distributions computed through constraint-based approaches such as Flux Balance Analysis. We illustrate our approach on the central carbon metabolism of Escherichia coli and on a metabolic model of human hepatocytes. The flux-dependent graphs under various environmental conditions and genetic perturbations exhibit systemic changes in their topological and community structure, which capture the re-routing of metabolic flows and the varying importance of specific reactions and pathways. By integrating constraint-based models and tools from network science, our framework allows the study of context-specific metabolic responses at a system level beyond standard pathway descriptions.
Issue Date: 14-Aug-2018
Date of Acceptance: 3-Jul-2018
URI: http://hdl.handle.net/10044/1/62038
DOI: https://dx.doi.org/10.1038/s41540-018-0067-y
ISSN: 2056-7189
Publisher: Nature Publishing Group
Journal / Book Title: npj Systems Biology and Applications
Volume: 4
Copyright Statement: © The Author(s) 2018. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article ’ s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article ’ s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons. org/licenses/by/4.0/ .
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
Human Frontier Science Program
Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/I017267/1
EP/I032223/1
RGY-0076/2015
EP/N014529/1
Keywords: q-bio.MN
cs.SI
physics.soc-ph
Publication Status: Published
Article Number: ARTN 32
Appears in Collections:Mathematics
Applied Mathematics and Mathematical Physics
Faculty of Natural Sciences