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Integrated analysis of metabolic phenotypes in Saccharomyces cerevisiae

BACKGROUND: The yeast Saccharomyces cerevisiae is an important microorganism for both industrial processes and scientific research. Consequently, there have been extensive efforts to characterize its cellular processes. In order to fully understand the relationship between yeast's genome and it...

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Autores principales: Duarte, Natalie C, Palsson, Bernhard Ø, Fu, Pengcheng
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2004
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC520746/
https://www.ncbi.nlm.nih.gov/pubmed/15355549
http://dx.doi.org/10.1186/1471-2164-5-63
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author Duarte, Natalie C
Palsson, Bernhard Ø
Fu, Pengcheng
author_facet Duarte, Natalie C
Palsson, Bernhard Ø
Fu, Pengcheng
author_sort Duarte, Natalie C
collection PubMed
description BACKGROUND: The yeast Saccharomyces cerevisiae is an important microorganism for both industrial processes and scientific research. Consequently, there have been extensive efforts to characterize its cellular processes. In order to fully understand the relationship between yeast's genome and its physiology, the stockpiles of diverse biological data sets that describe its cellular components and phenotypic behavior must be integrated at the genome-scale. Genome-scale metabolic networks have been reconstructed for several microorganisms, including S. cerevisiae, and the properties of these networks have been successfully analyzed using a variety of constraint-based methods. Phenotypic phase plane analysis is a constraint-based method which provides a global view of how optimal growth rates are affected by changes in two environmental variables such as a carbon and an oxygen uptake rate. Some applications of phenotypic phase plane analysis include the study of optimal growth rates and of network capacity and function. RESULTS: In this study, the Saccharomyces cerevisiae genome-scale metabolic network was used to formulate a phenotypic phase plane that displays the maximum allowable growth rate and distinct patterns of metabolic pathway utilization for all combinations of glucose and oxygen uptake rates. In silico predictions of growth rate and secretion rates and in vivo data for three separate growth conditions (aerobic glucose-limited, oxidative-fermentative, and microaerobic) were concordant. CONCLUSIONS: Taken together, this study examines the function and capacity of yeast's metabolic machinery and shows that the phenotypic phase plane can be used to accurately predict metabolic phenotypes and to interpret experimental data in the context of a genome-scale model.
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spelling pubmed-5207462004-10-01 Integrated analysis of metabolic phenotypes in Saccharomyces cerevisiae Duarte, Natalie C Palsson, Bernhard Ø Fu, Pengcheng BMC Genomics Research Article BACKGROUND: The yeast Saccharomyces cerevisiae is an important microorganism for both industrial processes and scientific research. Consequently, there have been extensive efforts to characterize its cellular processes. In order to fully understand the relationship between yeast's genome and its physiology, the stockpiles of diverse biological data sets that describe its cellular components and phenotypic behavior must be integrated at the genome-scale. Genome-scale metabolic networks have been reconstructed for several microorganisms, including S. cerevisiae, and the properties of these networks have been successfully analyzed using a variety of constraint-based methods. Phenotypic phase plane analysis is a constraint-based method which provides a global view of how optimal growth rates are affected by changes in two environmental variables such as a carbon and an oxygen uptake rate. Some applications of phenotypic phase plane analysis include the study of optimal growth rates and of network capacity and function. RESULTS: In this study, the Saccharomyces cerevisiae genome-scale metabolic network was used to formulate a phenotypic phase plane that displays the maximum allowable growth rate and distinct patterns of metabolic pathway utilization for all combinations of glucose and oxygen uptake rates. In silico predictions of growth rate and secretion rates and in vivo data for three separate growth conditions (aerobic glucose-limited, oxidative-fermentative, and microaerobic) were concordant. CONCLUSIONS: Taken together, this study examines the function and capacity of yeast's metabolic machinery and shows that the phenotypic phase plane can be used to accurately predict metabolic phenotypes and to interpret experimental data in the context of a genome-scale model. BioMed Central 2004-09-08 /pmc/articles/PMC520746/ /pubmed/15355549 http://dx.doi.org/10.1186/1471-2164-5-63 Text en Copyright © 2004 Duarte et al; 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
Duarte, Natalie C
Palsson, Bernhard Ø
Fu, Pengcheng
Integrated analysis of metabolic phenotypes in Saccharomyces cerevisiae
title Integrated analysis of metabolic phenotypes in Saccharomyces cerevisiae
title_full Integrated analysis of metabolic phenotypes in Saccharomyces cerevisiae
title_fullStr Integrated analysis of metabolic phenotypes in Saccharomyces cerevisiae
title_full_unstemmed Integrated analysis of metabolic phenotypes in Saccharomyces cerevisiae
title_short Integrated analysis of metabolic phenotypes in Saccharomyces cerevisiae
title_sort integrated analysis of metabolic phenotypes in saccharomyces cerevisiae
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC520746/
https://www.ncbi.nlm.nih.gov/pubmed/15355549
http://dx.doi.org/10.1186/1471-2164-5-63
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