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Improved computational performance of MFA using elementary metabolite units and flux coupling

Paper ID Volume ID Publish Year Pages File Format Full-Text
31807 44840 2010 6 PDF Available
Title
Improved computational performance of MFA using elementary metabolite units and flux coupling
Abstract

Extending the scope of isotope mapping models becomes increasingly important in order to analyze strains and drive improved product yields as more complex pathways are engineered into strains and as secondary metabolites are used as starting points for new products. Here we present how the elementary metabolite unit (EMU) framework and flux coupling significantly decrease the computational burden of metabolic flux analysis (MFA) when applied to large-scale metabolic models. We applied these techniques to a previously published isotope mapping model of Escherichia coli accounting for 238 reactions. We find that the combined use of EMU and flux coupling analysis leads to a ten-fold decrease in the number of variables in comparison to the original isotope distribution vector (IDV) version of the model. In addition, using OptMeas the task of identifying additional measurement choices to fully specify the flows in the metabolic network required only 2% of the computation time of the one using IDVs. The observed computational savings reveal the rapid progress in performing MFA with increasingly larger isotope models with the ultimate goal of handling genome-scale models of metabolism.

Keywords
Metabolic flux analysis; Isotope labeling; Optimization; Constraint-based modeling; Experimental design
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Publisher
Database: Elsevier - ScienceDirect
Journal: Metabolic Engineering - Volume 12, Issue 2, March 2010, Pages 123–128
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us