An exact arithmetic toolbox for a consistent and reproducible structural analysis of metabolic network models
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Author(s) • • •
Chindelevitch, Leonid
Trigg, Jason
Regev, Aviv
Berger Leighton, Bonnie
Date Issued
October 2014
Journal
Nature Communications
Publisher
Nature Publishing Group
Citation
Chindelevitch, Leonid, Jason Trigg, Aviv Regev, and Bonnie Berger. “An Exact Arithmetic Toolbox for a Consistent and Reproducible Structural Analysis of Metabolic Network Models.” Nature Communications 5 (October 7, 2014): 4893.
Version
Final published version
Abstract
Constraint-based models are currently the only methodology that allows the study of metabolism at the whole-genome scale. Flux balance analysis is commonly used to analyse constraint-based models. Curiously, the results of this analysis vary with the software being run, a situation that we show can be remedied by using exact rather than floating-point arithmetic. Here we introduce MONGOOSE, a toolbox for analysing the structure of constraint-based metabolic models in exact arithmetic. We apply MONGOOSE to the analysis of 98 existing metabolic network models and find that the biomass reaction is surprisingly blocked (unable to sustain non-zero flux) in nearly half of them. We propose a principled approach for unblocking these reactions and extend it to the problems of identifying essential and synthetic lethal reactions and minimal media. Our structural insights enable a systematic study of constraint-based metabolic models, yielding a deeper understanding of their possibilities and limitations.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Mathematics
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1038/ncomms5893