Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.

Primarily used for metabolic engineering and synthetic biology, genome-scale metabolic modeling shows tremendous potential as a tool for fundamental research and curation of metabolism. Through a novel integration of flux balance analysis and genetic algorithms, a strategy to curate metabolic networ...

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Autores principales:	Eddy J Bautista, Joseph Zinski, Steven M Szczepanek, Erik L Johnson, Edan R Tulman, Wei-Mei Ching, Steven J Geary, Ranjan Srivastava
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/06aadc39c61142288c534dfd7560c155
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spelling	oai:doaj.org-article:06aadc39c61142288c534dfd7560c1552021-11-18T05:53:36ZSemi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.1553-734X1553-735810.1371/journal.pcbi.1003208https://doaj.org/article/06aadc39c61142288c534dfd7560c1552013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24039564/pdf/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Primarily used for metabolic engineering and synthetic biology, genome-scale metabolic modeling shows tremendous potential as a tool for fundamental research and curation of metabolism. Through a novel integration of flux balance analysis and genetic algorithms, a strategy to curate metabolic networks and facilitate identification of metabolic pathways that may not be directly inferable solely from genome annotation was developed. Specifically, metabolites involved in unknown reactions can be determined, and potentially erroneous pathways can be identified. The procedure developed allows for new fundamental insight into metabolism, as well as acting as a semi-automated curation methodology for genome-scale metabolic modeling. To validate the methodology, a genome-scale metabolic model for the bacterium Mycoplasma gallisepticum was created. Several reactions not predicted by the genome annotation were postulated and validated via the literature. The model predicted an average growth rate of 0.358±0.12[Formula: see text], closely matching the experimentally determined growth rate of M. gallisepticum of 0.244±0.03[Formula: see text]. This work presents a powerful algorithm for facilitating the identification and curation of previously known and new metabolic pathways, as well as presenting the first genome-scale reconstruction of M. gallisepticum.Eddy J BautistaJoseph ZinskiSteven M SzczepanekErik L JohnsonEdan R TulmanWei-Mei ChingSteven J GearyRanjan SrivastavaPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 9, Iss 9, p e1003208 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Eddy J Bautista Joseph Zinski Steven M Szczepanek Erik L Johnson Edan R Tulman Wei-Mei Ching Steven J Geary Ranjan Srivastava Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.
description	Primarily used for metabolic engineering and synthetic biology, genome-scale metabolic modeling shows tremendous potential as a tool for fundamental research and curation of metabolism. Through a novel integration of flux balance analysis and genetic algorithms, a strategy to curate metabolic networks and facilitate identification of metabolic pathways that may not be directly inferable solely from genome annotation was developed. Specifically, metabolites involved in unknown reactions can be determined, and potentially erroneous pathways can be identified. The procedure developed allows for new fundamental insight into metabolism, as well as acting as a semi-automated curation methodology for genome-scale metabolic modeling. To validate the methodology, a genome-scale metabolic model for the bacterium Mycoplasma gallisepticum was created. Several reactions not predicted by the genome annotation were postulated and validated via the literature. The model predicted an average growth rate of 0.358±0.12[Formula: see text], closely matching the experimentally determined growth rate of M. gallisepticum of 0.244±0.03[Formula: see text]. This work presents a powerful algorithm for facilitating the identification and curation of previously known and new metabolic pathways, as well as presenting the first genome-scale reconstruction of M. gallisepticum.
format	article
author	Eddy J Bautista Joseph Zinski Steven M Szczepanek Erik L Johnson Edan R Tulman Wei-Mei Ching Steven J Geary Ranjan Srivastava
author_facet	Eddy J Bautista Joseph Zinski Steven M Szczepanek Erik L Johnson Edan R Tulman Wei-Mei Ching Steven J Geary Ranjan Srivastava
author_sort	Eddy J Bautista
title	Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.
title_short	Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.
title_full	Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.
title_fullStr	Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.
title_full_unstemmed	Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.
title_sort	semi-automated curation of metabolic models via flux balance analysis: a case study with mycoplasma gallisepticum.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/06aadc39c61142288c534dfd7560c155
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Semi-automated curation of metabolic models via flux balance analysis: a case study with Mycoplasma gallisepticum.

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