Using Systems Engineering to Reconstruct, Analyze and Redesign Metabolism

Publisher Summary This chapter describes the process of using stems engineering to reconstruct, analyze, and redesign metabolism. Systems engineering computational techniques and particularly mathematical programming are increasingly being used to not only optimize metabolism for targeted overproductions but also for streamlining the process of metabolic model creation and curation. Currently, there exists about twenty different microbial and eukaryotic metabolic reconstructions (for example, Escherichia coli, Saccharomyces cerevisiae, and Bacillus subtilis) with many more under development. All of these reconstructions are inherently incomplete with some functionalities missing or erroneously added because of the lack of experimental and/or homology information. This chapter introduces optimization-based procedures (that is., GapFind and GapFill) to identify and eliminate network gaps in these reconstructions. These gaps are manifested as metabolites that are lacking either production and/or consumption pathways. Under steady-state conditions these metabolites form isolated parts of the model that cannot carry any metabolic flow. In addition to connectivity, genome-scale metabolic reconstructions are generally validated by comparing in silico growth predictions for different single gene deletion mutants under different carbon substrates with in vivo growth data. These comparisons results in two types of model-prediction inconsistencies; either the model predicts growth when no growth is observed in the experiment or the model predicts no growth when the experiment reveals growth.