title: Refining carbon flux paths using atomic trace data.
abstract: BACKGROUND
  Pathway analysis tools are a powerful strategy to analyze 'omics' data in the field of systems biology. From a metabolic perspective, several pathway definitions can be found in the literature, each one appropriate for a particular study. Recently, a novel pathway concept termed carbon flux paths (CFPs) was introduced and benchmarked against existing approaches, showing a clear advantage for finding linear pathways from a given source to target metabolite. CFPs are simple paths in a metabolite-metabolite graph that satisfy typical constraints in stoichiometric models: mass balancing and thermodynamics (irreversibility). In addition, CFPs guarantee carbon exchange in each of their intermediate steps, but not between the source and the target metabolites and consequently false positive solutions may arise. These pathways often lack biological interest, particularly when studying biosynthetic or degradation routes of a metabolite. To overcome this issue, we amend the formulation in CFP, so as to account for atomic fate information. This approach is termed atomic CFP (aCFP).
  
  
  RESULTS
  By means of a side-by-side comparison in a medium scale metabolic network in Escherichia Coli, we show that aCFP provides more biologically relevant pathways than CFP, because canonical pathways are more easily recovered, which reflects the benefits of removing false positives. In addition, we demonstrate that aCFP can be successfully applied to genome-scale metabolic networks. As the quality of genome-scale atomic reconstruction is improved, methods such as the one presented here will undoubtedly be of value to interpret 'omics' data.
authors.affiliation: CEIT and TECNUN, University of Navarra, Manuel de Lardizabal 15, 20018 San Sebastian, Spain and Mathematical Sciences, Brunel University, Kingston Lane, UB8 3PH, Uxbridge, UK.
authors.forename: Jon
authors.initials: J
authors.lastname: Pey
authors.forename: Francisco J
authors.initials: FJ
authors.lastname: Planes
authors.forename: John E
authors.initials: JE
authors.lastname: Beasley
mesh_terms: D002244:Carbon / Q000032:analysis*; D057486:Carbon Cycle; D004926:Escherichia coli / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D016680:Genome, Bacterial; D053858:Metabolic Networks and Pathways / Q000235:genetics; D011770:Pyruvate Kinase / Q000378:metabolism
chemical_list: D002244:Carbon; D011770:Pyruvate Kinase