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Design of Optimally Constructed Metabolic Networks of Minimal Functionality
BACKGROUND: Metabolic engineering aims to design microorganisms that will generate a product of interest at high yield. Thus, a variety of in silico modeling strategies has been applied successfully, including the concepts of elementary flux modes (EFMs) and constrained minimal cut sets (cMCSs). The...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3965433/ https://www.ncbi.nlm.nih.gov/pubmed/24667792 http://dx.doi.org/10.1371/journal.pone.0092583 |
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author | Ruckerbauer, David E. Jungreuthmayer, Christian Zanghellini, Jürgen |
author_facet | Ruckerbauer, David E. Jungreuthmayer, Christian Zanghellini, Jürgen |
author_sort | Ruckerbauer, David E. |
collection | PubMed |
description | BACKGROUND: Metabolic engineering aims to design microorganisms that will generate a product of interest at high yield. Thus, a variety of in silico modeling strategies has been applied successfully, including the concepts of elementary flux modes (EFMs) and constrained minimal cut sets (cMCSs). The EFMs (minimal, steady state pathways through the system) can be calculated given a metabolic model. cMCSs are sets of reaction deletions in such a network that will allow desired pathways to survive and disable undesired ones (e.g., those with low product secretion or low growth rates). Grouping the modes into desired and undesired categories had to be done manually until now. RESULTS: Although the optimal solution for a given set of pathways will always be found with the currently available tools, manual selection may lead to a sub-optimal solution with respect to a metabolic engineering target. A small change in the selection of modes can reduce the number of necessary deletions while only slightly reducing production. Based on our recently introduced formulation of cut set calculations using binary linear programming, we suggest an algorithm that does not require manual selection of the desired pathways. CONCLUSIONS: We demonstrated the principle of our algorithm with the help of a small toy network and applied it to a model of E. coli using different design objectives. Furthermore we validated our method by reproducing previously obtained results without requiring manual grouping of modes. |
format | Online Article Text |
id | pubmed-3965433 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-39654332014-03-27 Design of Optimally Constructed Metabolic Networks of Minimal Functionality Ruckerbauer, David E. Jungreuthmayer, Christian Zanghellini, Jürgen PLoS One Research Article BACKGROUND: Metabolic engineering aims to design microorganisms that will generate a product of interest at high yield. Thus, a variety of in silico modeling strategies has been applied successfully, including the concepts of elementary flux modes (EFMs) and constrained minimal cut sets (cMCSs). The EFMs (minimal, steady state pathways through the system) can be calculated given a metabolic model. cMCSs are sets of reaction deletions in such a network that will allow desired pathways to survive and disable undesired ones (e.g., those with low product secretion or low growth rates). Grouping the modes into desired and undesired categories had to be done manually until now. RESULTS: Although the optimal solution for a given set of pathways will always be found with the currently available tools, manual selection may lead to a sub-optimal solution with respect to a metabolic engineering target. A small change in the selection of modes can reduce the number of necessary deletions while only slightly reducing production. Based on our recently introduced formulation of cut set calculations using binary linear programming, we suggest an algorithm that does not require manual selection of the desired pathways. CONCLUSIONS: We demonstrated the principle of our algorithm with the help of a small toy network and applied it to a model of E. coli using different design objectives. Furthermore we validated our method by reproducing previously obtained results without requiring manual grouping of modes. Public Library of Science 2014-03-25 /pmc/articles/PMC3965433/ /pubmed/24667792 http://dx.doi.org/10.1371/journal.pone.0092583 Text en © 2014 Ruckerbauer et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Ruckerbauer, David E. Jungreuthmayer, Christian Zanghellini, Jürgen Design of Optimally Constructed Metabolic Networks of Minimal Functionality |
title | Design of Optimally Constructed Metabolic Networks of Minimal Functionality |
title_full | Design of Optimally Constructed Metabolic Networks of Minimal Functionality |
title_fullStr | Design of Optimally Constructed Metabolic Networks of Minimal Functionality |
title_full_unstemmed | Design of Optimally Constructed Metabolic Networks of Minimal Functionality |
title_short | Design of Optimally Constructed Metabolic Networks of Minimal Functionality |
title_sort | design of optimally constructed metabolic networks of minimal functionality |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3965433/ https://www.ncbi.nlm.nih.gov/pubmed/24667792 http://dx.doi.org/10.1371/journal.pone.0092583 |
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