PT  - JOURNAL ARTICLE
AU  - Mariano Beguerisse-Díaz
AU  - Gabriel Bosque
AU  - Diego Oyarzún
AU  - Jesús Picóo
AU  - Mauricio Barahona
TI  - Flux-dependent graphs for metabolic networks
AID  - 10.1101/290767
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 290767
4099  - http://biorxiv.org/content/early/2018/03/30/290767.short
4100  - http://biorxiv.org/content/early/2018/03/30/290767.full
AB  - Cells adapt their metabolic fluxes in response to changes in the environment. We present a frame-work for the systematic construction of flux-based graphs derived from organism-wide metabolic networks. Our graphs encode the directionality of metabolic fluxes 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 environ-mental 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 topo-logical and community structure, which capture the re-routing of metabolic fluxes 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.