Understanding regulation of metabolism through feasibility analysis.

Understanding cellular regulation of metabolism is a major challenge in systems biology. Thus far, the main assumption was that enzyme levels are key regulators in metabolic networks. However, regulation analysis recently showed that metabolism is rarely controlled via enzyme levels only, but throug...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Emrah Nikerel, Jan Berkhout, Fengyuan Hu, Bas Teusink, Marcel J T Reinders, Dick de Ridder
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d2e3ac79b903456aae2f5835b33675dd
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:d2e3ac79b903456aae2f5835b33675dd
record_format	dspace
spelling	oai:doaj.org-article:d2e3ac79b903456aae2f5835b33675dd2021-11-18T07:13:03ZUnderstanding regulation of metabolism through feasibility analysis.1932-620310.1371/journal.pone.0039396https://doaj.org/article/d2e3ac79b903456aae2f5835b33675dd2012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22808034/?tool=EBIhttps://doaj.org/toc/1932-6203Understanding cellular regulation of metabolism is a major challenge in systems biology. Thus far, the main assumption was that enzyme levels are key regulators in metabolic networks. However, regulation analysis recently showed that metabolism is rarely controlled via enzyme levels only, but through non-obvious combinations of hierarchical (gene and enzyme levels) and metabolic regulation (mass action and allosteric interaction). Quantitative analyses relating changes in metabolic fluxes to changes in transcript or protein levels have revealed a remarkable lack of understanding of the regulation of these networks. We study metabolic regulation via feasibility analysis (FA). Inspired by the constraint-based approach of Flux Balance Analysis, FA incorporates a model describing kinetic interactions between molecules. We enlarge the portfolio of objectives for the cell by defining three main physiologically relevant objectives for the cell: function, robustness and temporal responsiveness. We postulate that the cell assumes one or a combination of these objectives and search for enzyme levels necessary to achieve this. We call the subspace of feasible enzyme levels the feasible enzyme space. Once this space is constructed, we can study how different objectives may (if possible) be combined, or evaluate the conditions at which the cells are faced with a trade-off among those. We apply FA to the experimental scenario of long-term carbon limited chemostat cultivation of yeast cells, studying how metabolism evolves optimally. Cells employ a mixed strategy composed of increasing enzyme levels for glucose uptake and hexokinase and decreasing levels of the remaining enzymes. This trade-off renders the cells specialized in this low-carbon flux state to compete for the available glucose and get rid of over-overcapacity. Overall, we show that FA is a powerful tool for systems biologists to study regulation of metabolism, interpret experimental data and evaluate hypotheses.Emrah NikerelJan BerkhoutFengyuan HuBas TeusinkMarcel J T ReindersDick de RidderPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 7, p e39396 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Emrah Nikerel Jan Berkhout Fengyuan Hu Bas Teusink Marcel J T Reinders Dick de Ridder Understanding regulation of metabolism through feasibility analysis.
description	Understanding cellular regulation of metabolism is a major challenge in systems biology. Thus far, the main assumption was that enzyme levels are key regulators in metabolic networks. However, regulation analysis recently showed that metabolism is rarely controlled via enzyme levels only, but through non-obvious combinations of hierarchical (gene and enzyme levels) and metabolic regulation (mass action and allosteric interaction). Quantitative analyses relating changes in metabolic fluxes to changes in transcript or protein levels have revealed a remarkable lack of understanding of the regulation of these networks. We study metabolic regulation via feasibility analysis (FA). Inspired by the constraint-based approach of Flux Balance Analysis, FA incorporates a model describing kinetic interactions between molecules. We enlarge the portfolio of objectives for the cell by defining three main physiologically relevant objectives for the cell: function, robustness and temporal responsiveness. We postulate that the cell assumes one or a combination of these objectives and search for enzyme levels necessary to achieve this. We call the subspace of feasible enzyme levels the feasible enzyme space. Once this space is constructed, we can study how different objectives may (if possible) be combined, or evaluate the conditions at which the cells are faced with a trade-off among those. We apply FA to the experimental scenario of long-term carbon limited chemostat cultivation of yeast cells, studying how metabolism evolves optimally. Cells employ a mixed strategy composed of increasing enzyme levels for glucose uptake and hexokinase and decreasing levels of the remaining enzymes. This trade-off renders the cells specialized in this low-carbon flux state to compete for the available glucose and get rid of over-overcapacity. Overall, we show that FA is a powerful tool for systems biologists to study regulation of metabolism, interpret experimental data and evaluate hypotheses.
format	article
author	Emrah Nikerel Jan Berkhout Fengyuan Hu Bas Teusink Marcel J T Reinders Dick de Ridder
author_facet	Emrah Nikerel Jan Berkhout Fengyuan Hu Bas Teusink Marcel J T Reinders Dick de Ridder
author_sort	Emrah Nikerel
title	Understanding regulation of metabolism through feasibility analysis.
title_short	Understanding regulation of metabolism through feasibility analysis.
title_full	Understanding regulation of metabolism through feasibility analysis.
title_fullStr	Understanding regulation of metabolism through feasibility analysis.
title_full_unstemmed	Understanding regulation of metabolism through feasibility analysis.
title_sort	understanding regulation of metabolism through feasibility analysis.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/d2e3ac79b903456aae2f5835b33675dd
work_keys_str_mv	AT emrahnikerel understandingregulationofmetabolismthroughfeasibilityanalysis AT janberkhout understandingregulationofmetabolismthroughfeasibilityanalysis AT fengyuanhu understandingregulationofmetabolismthroughfeasibilityanalysis AT basteusink understandingregulationofmetabolismthroughfeasibilityanalysis AT marceljtreinders understandingregulationofmetabolismthroughfeasibilityanalysis AT dickderidder understandingregulationofmetabolismthroughfeasibilityanalysis
_version_	1718423819997151232

Understanding regulation of metabolism through feasibility analysis.

Ejemplares similares