The genome-scale metabolic extreme pathway structure in Haemophilus influenzae shows significant network redundancy.

TitleThe genome-scale metabolic extreme pathway structure in Haemophilus influenzae shows significant network redundancy.
Publication TypeJournal Article
Year of Publication2002
AuthorsPapin JA, Price ND, Edwards JS, Palsson B BØ
JournalJ Theor Biol
Date Published2002 Mar 7
KeywordsAmino Acids, Carbon, Genome, Bacterial, Genotype, Haemophilus influenzae, Models, Biological, Signal Transduction

Genome-scale metabolic networks can be characterized by a set of systemically independent and unique extreme pathways. These extreme pathways span a convex, high-dimensional space that circumscribes all potential steady-state flux distributions achievable by the defined metabolic network. Genome-scale extreme pathways associated with the production of non-essential amino acids in Haemophilus influenzae were computed. They offer valuable insight into the functioning of its metabolic network. Three key results were obtained. First, there were multiple internal flux maps corresponding to externally indistinguishable states. It was shown that there was an average of 37 internal states per unique exchange flux vector in H. influenzae when the network was used to produce a single amino acid while allowing carbon dioxide and acetate as carbon sinks. With the inclusion of succinate as an additional output, this ratio increased to 52, a 40% increase. Second, an analysis of the carbon fates illustrated that the extreme pathways were non-uniformly distributed across the carbon fate spectrum. In the detailed case study, 45% of the distinct carbon fate values associated with lysine production represented 85% of the extreme pathways. Third, this distribution fell between distinct systemic constraints. For lysine production, the carbon fate values that represented 85% of the pathways described above corresponded to only 2 distinct ratios of 1:1 and 4:1 between carbon dioxide and acetate. The present study analysed single outputs from one organism, and provides a start to genome-scale extreme pathways studies. These emergent system-level characterizations show the significance of metabolic extreme pathway analysis at the genome-scale.

PubMed URL
Alternate JournalJ. Theor. Biol.
PubMed ID12051985