(623g) Host Selection for Synthetic Pathways Using a Genome-Scale Model Database | AIChE

(623g) Host Selection for Synthetic Pathways Using a Genome-Scale Model Database


Senger, R. S. - Presenter, Virginia Tech

The number of available genome-scale models is growing exponentially, and the standards and formats in which they are published remain diverse.  This has made it difficult for the computational biologist to compare several genome-scale models side-by-side.  One notable application for this analysis is host selection for a novel synthetic pathway based on the metabolic capabilities of several organisms.  To do this, genome-scale model information must be organized and stored in not only a retrievable but also an easily modifiable format.  Several databases have been developed over the past decade for storing and using the genomic, enzymatic, metabolic pathway, and expression/phenotypic data.  During this time, genome-scale models have become established as a systems-level tool for integrating this information. Thus, newer databases, such as the BiGG database, The SEED, MEMOSys (and others soon to be published) have been created to house metabolic network reconstructions.  Here, we present the first database of genome-scale models that allows the user to incorporate user-defined synthetic pathways to any model and retrieve a standard or modified model in Systems Biology Markup Language (SBML) format.  This database is of special interest to metabolic engineers and systems biologists since it can (i) act as a platform for exporting existing genome-scale models, with thermodynamic and pKa data, and modifying models with updated biochemical and phenotypic data, (ii) it can be used to compare reactions, genes, and compounds contained in different organisms and give insights into the similarities and discrepancies of existing models, and (iii) it can be used for synthetic pathway incorporation and prediction of potential pathway usage.  Over 20 genome-scale models have been added to the database to date.  Here, we will present a novel application of host selection for optimal expression of a given synthetic pathway to demonstrate the usefulness of the database approach to this important problem.