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Flux Imbalance Analysis and the Sensitivity of Cellular Growth to Changes in Metabolite Pools
Stoichiometric models of metabolism, such as flux balance analysis (FBA), are classically applied to predicting steady state rates - or fluxes - of metabolic reactions in genome-scale metabolic networks. Here we revisit the central assumption of FBA, i.e. that intracellular metabolites are at steady...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3757068/ https://www.ncbi.nlm.nih.gov/pubmed/24009492 http://dx.doi.org/10.1371/journal.pcbi.1003195 |
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author | Reznik, Ed Mehta, Pankaj Segrè, Daniel |
author_facet | Reznik, Ed Mehta, Pankaj Segrè, Daniel |
author_sort | Reznik, Ed |
collection | PubMed |
description | Stoichiometric models of metabolism, such as flux balance analysis (FBA), are classically applied to predicting steady state rates - or fluxes - of metabolic reactions in genome-scale metabolic networks. Here we revisit the central assumption of FBA, i.e. that intracellular metabolites are at steady state, and show that deviations from flux balance (i.e. flux imbalances) are informative of some features of in vivo metabolite concentrations. Mathematically, the sensitivity of FBA to these flux imbalances is captured by a native feature of linear optimization, the dual problem, and its corresponding variables, known as shadow prices. First, using recently published data on chemostat growth of Saccharomyces cerevisae under different nutrient limitations, we show that shadow prices anticorrelate with experimentally measured degrees of growth limitation of intracellular metabolites. We next hypothesize that metabolites which are limiting for growth (and thus have very negative shadow price) cannot vary dramatically in an uncontrolled way, and must respond rapidly to perturbations. Using a collection of published datasets monitoring the time-dependent metabolomic response of Escherichia coli to carbon and nitrogen perturbations, we test this hypothesis and find that metabolites with negative shadow price indeed show lower temporal variation following a perturbation than metabolites with zero shadow price. Finally, we illustrate the broader applicability of flux imbalance analysis to other constraint-based methods. In particular, we explore the biological significance of shadow prices in a constraint-based method for integrating gene expression data with a stoichiometric model. In this case, shadow prices point to metabolites that should rise or drop in concentration in order to increase consistency between flux predictions and gene expression data. In general, these results suggest that the sensitivity of metabolic optima to violations of the steady state constraints carries biologically significant information on the processes that control intracellular metabolites in the cell. |
format | Online Article Text |
id | pubmed-3757068 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-37570682013-09-05 Flux Imbalance Analysis and the Sensitivity of Cellular Growth to Changes in Metabolite Pools Reznik, Ed Mehta, Pankaj Segrè, Daniel PLoS Comput Biol Research Article Stoichiometric models of metabolism, such as flux balance analysis (FBA), are classically applied to predicting steady state rates - or fluxes - of metabolic reactions in genome-scale metabolic networks. Here we revisit the central assumption of FBA, i.e. that intracellular metabolites are at steady state, and show that deviations from flux balance (i.e. flux imbalances) are informative of some features of in vivo metabolite concentrations. Mathematically, the sensitivity of FBA to these flux imbalances is captured by a native feature of linear optimization, the dual problem, and its corresponding variables, known as shadow prices. First, using recently published data on chemostat growth of Saccharomyces cerevisae under different nutrient limitations, we show that shadow prices anticorrelate with experimentally measured degrees of growth limitation of intracellular metabolites. We next hypothesize that metabolites which are limiting for growth (and thus have very negative shadow price) cannot vary dramatically in an uncontrolled way, and must respond rapidly to perturbations. Using a collection of published datasets monitoring the time-dependent metabolomic response of Escherichia coli to carbon and nitrogen perturbations, we test this hypothesis and find that metabolites with negative shadow price indeed show lower temporal variation following a perturbation than metabolites with zero shadow price. Finally, we illustrate the broader applicability of flux imbalance analysis to other constraint-based methods. In particular, we explore the biological significance of shadow prices in a constraint-based method for integrating gene expression data with a stoichiometric model. In this case, shadow prices point to metabolites that should rise or drop in concentration in order to increase consistency between flux predictions and gene expression data. In general, these results suggest that the sensitivity of metabolic optima to violations of the steady state constraints carries biologically significant information on the processes that control intracellular metabolites in the cell. Public Library of Science 2013-08-29 /pmc/articles/PMC3757068/ /pubmed/24009492 http://dx.doi.org/10.1371/journal.pcbi.1003195 Text en © 2013 Reznik 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 Reznik, Ed Mehta, Pankaj Segrè, Daniel Flux Imbalance Analysis and the Sensitivity of Cellular Growth to Changes in Metabolite Pools |
title | Flux Imbalance Analysis and the Sensitivity of Cellular Growth to Changes in Metabolite Pools |
title_full | Flux Imbalance Analysis and the Sensitivity of Cellular Growth to Changes in Metabolite Pools |
title_fullStr | Flux Imbalance Analysis and the Sensitivity of Cellular Growth to Changes in Metabolite Pools |
title_full_unstemmed | Flux Imbalance Analysis and the Sensitivity of Cellular Growth to Changes in Metabolite Pools |
title_short | Flux Imbalance Analysis and the Sensitivity of Cellular Growth to Changes in Metabolite Pools |
title_sort | flux imbalance analysis and the sensitivity of cellular growth to changes in metabolite pools |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3757068/ https://www.ncbi.nlm.nih.gov/pubmed/24009492 http://dx.doi.org/10.1371/journal.pcbi.1003195 |
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