Design of optimally constructed metabolic networks of minimal functionality.

<h4>Background</h4>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 cu...

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Autores principales:	David E Ruckerbauer, Christian Jungreuthmayer, Jürgen Zanghellini
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6c8ec51ae95f40f6a4bba57f6ae90164
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spelling	oai:doaj.org-article:6c8ec51ae95f40f6a4bba57f6ae901642021-11-18T08:26:14ZDesign of optimally constructed metabolic networks of minimal functionality.1932-620310.1371/journal.pone.0092583https://doaj.org/article/6c8ec51ae95f40f6a4bba57f6ae901642014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24667792/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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.David E RuckerbauerChristian JungreuthmayerJürgen ZanghelliniPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 3, p e92583 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q David E Ruckerbauer Christian Jungreuthmayer Jürgen Zanghellini Design of optimally constructed metabolic networks of minimal functionality.
description	<h4>Background</h4>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.<h4>Results</h4>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.<h4>Conclusions</h4>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	article
author	David E Ruckerbauer Christian Jungreuthmayer Jürgen Zanghellini
author_facet	David E Ruckerbauer Christian Jungreuthmayer Jürgen Zanghellini
author_sort	David E Ruckerbauer
title	Design of optimally constructed metabolic networks of minimal functionality.
title_short	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_sort	design of optimally constructed metabolic networks of minimal functionality.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/6c8ec51ae95f40f6a4bba57f6ae90164
work_keys_str_mv	AT davideruckerbauer designofoptimallyconstructedmetabolicnetworksofminimalfunctionality AT christianjungreuthmayer designofoptimallyconstructedmetabolicnetworksofminimalfunctionality AT jurgenzanghellini designofoptimallyconstructedmetabolicnetworksofminimalfunctionality
_version_	1718421807955968000

Design of optimally constructed metabolic networks of minimal functionality.

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