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Redirector: Designing Cell Factories by Reconstructing the Metabolic Objective

Advances in computational metabolic optimization are required to realize the full potential of new in vivo metabolic engineering technologies by bridging the gap between computational design and strain development. We present Redirector, a new Flux Balance Analysis-based framework for identifying en...

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Detalles Bibliográficos
Autores principales: Rockwell, Graham, Guido, Nicholas J., Church, George M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3547792/
https://www.ncbi.nlm.nih.gov/pubmed/23341769
http://dx.doi.org/10.1371/journal.pcbi.1002882
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author Rockwell, Graham
Guido, Nicholas J.
Church, George M.
author_facet Rockwell, Graham
Guido, Nicholas J.
Church, George M.
author_sort Rockwell, Graham
collection PubMed
description Advances in computational metabolic optimization are required to realize the full potential of new in vivo metabolic engineering technologies by bridging the gap between computational design and strain development. We present Redirector, a new Flux Balance Analysis-based framework for identifying engineering targets to optimize metabolite production in complex pathways. Previous optimization frameworks have modeled metabolic alterations as directly controlling fluxes by setting particular flux bounds. Redirector develops a more biologically relevant approach, modeling metabolic alterations as changes in the balance of metabolic objectives in the system. This framework iteratively selects enzyme targets, adds the associated reaction fluxes to the metabolic objective, thereby incentivizing flux towards the production of a metabolite of interest. These adjustments to the objective act in competition with cellular growth and represent up-regulation and down-regulation of enzyme mediated reactions. Using the iAF1260 E. coli metabolic network model for optimization of fatty acid production as a test case, Redirector generates designs with as many as 39 simultaneous and 111 unique engineering targets. These designs discover proven in vivo targets, novel supporting pathways and relevant interdependencies, many of which cannot be predicted by other methods. Redirector is available as open and free software, scalable to computational resources, and powerful enough to find all known enzyme targets for fatty acid production.
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spelling pubmed-35477922013-01-22 Redirector: Designing Cell Factories by Reconstructing the Metabolic Objective Rockwell, Graham Guido, Nicholas J. Church, George M. PLoS Comput Biol Research Article Advances in computational metabolic optimization are required to realize the full potential of new in vivo metabolic engineering technologies by bridging the gap between computational design and strain development. We present Redirector, a new Flux Balance Analysis-based framework for identifying engineering targets to optimize metabolite production in complex pathways. Previous optimization frameworks have modeled metabolic alterations as directly controlling fluxes by setting particular flux bounds. Redirector develops a more biologically relevant approach, modeling metabolic alterations as changes in the balance of metabolic objectives in the system. This framework iteratively selects enzyme targets, adds the associated reaction fluxes to the metabolic objective, thereby incentivizing flux towards the production of a metabolite of interest. These adjustments to the objective act in competition with cellular growth and represent up-regulation and down-regulation of enzyme mediated reactions. Using the iAF1260 E. coli metabolic network model for optimization of fatty acid production as a test case, Redirector generates designs with as many as 39 simultaneous and 111 unique engineering targets. These designs discover proven in vivo targets, novel supporting pathways and relevant interdependencies, many of which cannot be predicted by other methods. Redirector is available as open and free software, scalable to computational resources, and powerful enough to find all known enzyme targets for fatty acid production. Public Library of Science 2013-01-17 /pmc/articles/PMC3547792/ /pubmed/23341769 http://dx.doi.org/10.1371/journal.pcbi.1002882 Text en © 2013 Rockwell 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
Rockwell, Graham
Guido, Nicholas J.
Church, George M.
Redirector: Designing Cell Factories by Reconstructing the Metabolic Objective
title Redirector: Designing Cell Factories by Reconstructing the Metabolic Objective
title_full Redirector: Designing Cell Factories by Reconstructing the Metabolic Objective
title_fullStr Redirector: Designing Cell Factories by Reconstructing the Metabolic Objective
title_full_unstemmed Redirector: Designing Cell Factories by Reconstructing the Metabolic Objective
title_short Redirector: Designing Cell Factories by Reconstructing the Metabolic Objective
title_sort redirector: designing cell factories by reconstructing the metabolic objective
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3547792/
https://www.ncbi.nlm.nih.gov/pubmed/23341769
http://dx.doi.org/10.1371/journal.pcbi.1002882
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