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Gap-filling analysis of the iJO1366 Escherichia coli metabolic network reconstruction for discovery of metabolic functions

BACKGROUND: The iJO1366 reconstruction of the metabolic network of Escherichia coli is one of the most complete and accurate metabolic reconstructions available for any organism. Still, because our knowledge of even well-studied model organisms such as this one is incomplete, this network reconstruc...

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Autores principales: Orth, Jeffrey D, Palsson, BernhardØ
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3423039/
https://www.ncbi.nlm.nih.gov/pubmed/22548736
http://dx.doi.org/10.1186/1752-0509-6-30
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author Orth, Jeffrey D
Palsson, BernhardØ
author_facet Orth, Jeffrey D
Palsson, BernhardØ
author_sort Orth, Jeffrey D
collection PubMed
description BACKGROUND: The iJO1366 reconstruction of the metabolic network of Escherichia coli is one of the most complete and accurate metabolic reconstructions available for any organism. Still, because our knowledge of even well-studied model organisms such as this one is incomplete, this network reconstruction contains gaps and possible errors. There are a total of 208 blocked metabolites in iJO1366, representing gaps in the network. RESULTS: A new model improvement workflow was developed to compare model based phenotypic predictions to experimental data to fill gaps and correct errors. A Keio Collection based dataset of E. coli gene essentiality was obtained from literature data and compared to model predictions. The SMILEY algorithm was then used to predict the most likely missing reactions in the reconstructed network, adding reactions from a KEGG based universal set of metabolic reactions. The feasibility of these putative reactions was determined by comparing updated versions of the model to the experimental dataset, and genes were predicted for the most feasible reactions. CONCLUSIONS: Numerous improvements to the iJO1366 metabolic reconstruction were suggested by these analyses. Experiments were performed to verify several computational predictions, including a new mechanism for growth on myo-inositol. The other predictions made in this study should be experimentally verifiable by similar means. Validating all of the predictions made here represents a substantial but important undertaking.
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spelling pubmed-34230392012-08-21 Gap-filling analysis of the iJO1366 Escherichia coli metabolic network reconstruction for discovery of metabolic functions Orth, Jeffrey D Palsson, BernhardØ BMC Syst Biol Research Article BACKGROUND: The iJO1366 reconstruction of the metabolic network of Escherichia coli is one of the most complete and accurate metabolic reconstructions available for any organism. Still, because our knowledge of even well-studied model organisms such as this one is incomplete, this network reconstruction contains gaps and possible errors. There are a total of 208 blocked metabolites in iJO1366, representing gaps in the network. RESULTS: A new model improvement workflow was developed to compare model based phenotypic predictions to experimental data to fill gaps and correct errors. A Keio Collection based dataset of E. coli gene essentiality was obtained from literature data and compared to model predictions. The SMILEY algorithm was then used to predict the most likely missing reactions in the reconstructed network, adding reactions from a KEGG based universal set of metabolic reactions. The feasibility of these putative reactions was determined by comparing updated versions of the model to the experimental dataset, and genes were predicted for the most feasible reactions. CONCLUSIONS: Numerous improvements to the iJO1366 metabolic reconstruction were suggested by these analyses. Experiments were performed to verify several computational predictions, including a new mechanism for growth on myo-inositol. The other predictions made in this study should be experimentally verifiable by similar means. Validating all of the predictions made here represents a substantial but important undertaking. BioMed Central 2012-05-01 /pmc/articles/PMC3423039/ /pubmed/22548736 http://dx.doi.org/10.1186/1752-0509-6-30 Text en Copyright ©2012 Orth and Palsson; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Orth, Jeffrey D
Palsson, BernhardØ
Gap-filling analysis of the iJO1366 Escherichia coli metabolic network reconstruction for discovery of metabolic functions
title Gap-filling analysis of the iJO1366 Escherichia coli metabolic network reconstruction for discovery of metabolic functions
title_full Gap-filling analysis of the iJO1366 Escherichia coli metabolic network reconstruction for discovery of metabolic functions
title_fullStr Gap-filling analysis of the iJO1366 Escherichia coli metabolic network reconstruction for discovery of metabolic functions
title_full_unstemmed Gap-filling analysis of the iJO1366 Escherichia coli metabolic network reconstruction for discovery of metabolic functions
title_short Gap-filling analysis of the iJO1366 Escherichia coli metabolic network reconstruction for discovery of metabolic functions
title_sort gap-filling analysis of the ijo1366 escherichia coli metabolic network reconstruction for discovery of metabolic functions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3423039/
https://www.ncbi.nlm.nih.gov/pubmed/22548736
http://dx.doi.org/10.1186/1752-0509-6-30
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