Wanding Zhou1, Luay Nakhleh. 1. Department of Bioengineering, Rice University, Houston, TX, USA. wz4@rice.edu
Abstract
MOTIVATION: A metabolic graph represents the connectivity patterns of a metabolic system, and provides a powerful framework within which the organization of metabolic reactions can be analyzed and elucidated. A common practice is to prune (i.e. remove nodes and edges) the metabolic graph prior to any analysis in order to eliminate confounding signals from the representation. Currently, this pruning process is carried out in an ad hoc fashion, resulting in discrepancies and ambiguities across studies. RESULTS: We propose a biochemically informative criterion, the strength of chemical linkage (SCL), for a systematic pruning of metabolic graphs. By analyzing the metabolic graph of Escherichia coli, we show that thresholding SCL is powerful in selecting the conventional pathways' connectivity out of the raw network connectivity when the network is restricted to the reactions collected from these pathways. Further, we argue that the root of ambiguity in pruning metabolic graphs is in the continuity of the amount of chemical content that can be conserved in reaction transformation patterns. Finally, we demonstrate how biochemical pathways can be inferred efficiently if the search procedure is guided by SCL.
MOTIVATION: A metabolic graph represents the connectivity patterns of a metabolic system, and provides a powerful framework within which the organization of metabolic reactions can be analyzed and elucidated. A common practice is to prune (i.e. remove nodes and edges) the metabolic graph prior to any analysis in order to eliminate confounding signals from the representation. Currently, this pruning process is carried out in an ad hoc fashion, resulting in discrepancies and ambiguities across studies. RESULTS: We propose a biochemically informative criterion, the strength of chemical linkage (SCL), for a systematic pruning of metabolic graphs. By analyzing the metabolic graph of Escherichia coli, we show that thresholding SCL is powerful in selecting the conventional pathways' connectivity out of the raw network connectivity when the network is restricted to the reactions collected from these pathways. Further, we argue that the root of ambiguity in pruning metabolic graphs is in the continuity of the amount of chemical content that can be conserved in reaction transformation patterns. Finally, we demonstrate how biochemical pathways can be inferred efficiently if the search procedure is guided by SCL.
Authors: Markus J Herrgård; Neil Swainston; Paul Dobson; Warwick B Dunn; K Yalçin Arga; Mikko Arvas; Nils Blüthgen; Simon Borger; Roeland Costenoble; Matthias Heinemann; Michael Hucka; Nicolas Le Novère; Peter Li; Wolfram Liebermeister; Monica L Mo; Ana Paula Oliveira; Dina Petranovic; Stephen Pettifer; Evangelos Simeonidis; Kieran Smallbone; Irena Spasić; Dieter Weichart; Roger Brent; David S Broomhead; Hans V Westerhoff; Betül Kirdar; Merja Penttilä; Edda Klipp; Bernhard Ø Palsson; Uwe Sauer; Stephen G Oliver; Pedro Mendes; Jens Nielsen; Douglas B Kell Journal: Nat Biotechnol Date: 2008-10 Impact factor: 54.908