Abstract
The EcoCyc database is an online scientific database which provides an integrated view of the metabolic and regulatory network of the bacterium Escherichia coli K-12 and facilitates computational exploration of this important model organism. We have analysed the occurrence of dead end metabolites within the database – these are metabolites which lack the requisite reactions (either metabolic or transport) that would account for their production or consumption within the metabolic network. 127 dead end metabolites were identified from the 995 compounds that are contained within the EcoCyc metabolic network. Their presence reflects either a deficit in our representation of the network or in our knowledge of E. coli metabolism. Extensive literature searches resulted in the addition of 38 transport reactions and 3 metabolic reactions to the database and led to an improved representation of the pathway for Vitamin B12 salvage. 39 dead end metabolites were identified as components of reactions that are not physiologically relevant to E. coli K-12 – these reactions are properties of purified enzymes in vitro that would not be expected to occur in vivo. Our analysis led to improvements in the software that underpins the database and to the program that finds dead end metabolites within EcoCyc. The remaining dead end metabolites in the EcoCyc database likely represent deficiencies in our knowledge of E. coli metabolism.
Highlights
Symbolic systems biology is the application of logic-based computational methods to the systems-level analysis of an organism
A dead-end metabolite (DEM) is defined as a metabolite that is produced by the known metabolic reactions of an organism and has no reactions consuming it, or that is consumed by the metabolic reactions of an organism and has no known reactions producing it, and in both cases has no identified transporter (Figure 1)
In EcoCyc, metabolites may be reactants or products of reactions that occur within metabolic pathways defined within the database, or metabolites may form part of isolated reactions that are not contained within defined pathways
Summary
Symbolic systems biology is the application of logic-based computational methods to the systems-level analysis of an organism. Orphan enzymes are enzymes whose biochemical function has been demonstrated experimentally, but for which the associated gene has not been identified [2] In both cases, the explicit identification of holes in our knowledge spurs a whole series of new investigations. DEMs reflect a deficit or an error in how a metabolic database represents knowledge from the scientific literature, and alerts us to the need for further curation of the database. In other cases this systems-level analysis alerts us to areas where more experimental research is required. In the latter case DEMs act as signposts to the ‘known unknowns’ of metabolism
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