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Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach
BACKGROUND: Biological systems adapt to changing environments by reorganizing their cellular and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2759078/ https://www.ncbi.nlm.nih.gov/pubmed/19829699 http://dx.doi.org/10.1371/journal.pone.0007441 |
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author | Szymanski, Jedrzej Jozefczuk, Szymon Nikoloski, Zoran Selbig, Joachim Nikiforova, Victoria Catchpole, Gareth Willmitzer, Lothar |
author_facet | Szymanski, Jedrzej Jozefczuk, Szymon Nikoloski, Zoran Selbig, Joachim Nikiforova, Victoria Catchpole, Gareth Willmitzer, Lothar |
author_sort | Szymanski, Jedrzej |
collection | PubMed |
description | BACKGROUND: Biological systems adapt to changing environments by reorganizing their cellular and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underlying metabolic network. METHODOLOGY/PRINCIPAL FINDINGS: Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic condition-dependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple observations about the changes of metabolic concentrations. The approach was tested with Escherichia coli as a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diauxie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical pathways, and (3) independently of the response scale, based on their importance in the reorganization of the correlation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response. CONCLUSIONS/SIGNIFICANCE: Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-based approach does not rely on major changes in concentration to identify metabolites important for stress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches. |
format | Text |
id | pubmed-2759078 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-27590782009-10-15 Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach Szymanski, Jedrzej Jozefczuk, Szymon Nikoloski, Zoran Selbig, Joachim Nikiforova, Victoria Catchpole, Gareth Willmitzer, Lothar PLoS One Research Article BACKGROUND: Biological systems adapt to changing environments by reorganizing their cellular and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underlying metabolic network. METHODOLOGY/PRINCIPAL FINDINGS: Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic condition-dependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple observations about the changes of metabolic concentrations. The approach was tested with Escherichia coli as a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diauxie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical pathways, and (3) independently of the response scale, based on their importance in the reorganization of the correlation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response. CONCLUSIONS/SIGNIFICANCE: Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-based approach does not rely on major changes in concentration to identify metabolites important for stress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches. Public Library of Science 2009-10-15 /pmc/articles/PMC2759078/ /pubmed/19829699 http://dx.doi.org/10.1371/journal.pone.0007441 Text en Szymanski 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 Szymanski, Jedrzej Jozefczuk, Szymon Nikoloski, Zoran Selbig, Joachim Nikiforova, Victoria Catchpole, Gareth Willmitzer, Lothar Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach |
title | Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach |
title_full | Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach |
title_fullStr | Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach |
title_full_unstemmed | Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach |
title_short | Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach |
title_sort | stability of metabolic correlations under changing environmental conditions in escherichia coli – a systems approach |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2759078/ https://www.ncbi.nlm.nih.gov/pubmed/19829699 http://dx.doi.org/10.1371/journal.pone.0007441 |
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