English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli - A Systems Approach

Szymanski, J., Jozefczuk, S., Nikoloski, Z., Selbig, J., Nikiforova, V., Catchpole, G., et al. (2009). Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli - A Systems Approach. PLoS One, 4(10), e7441. doi:10.1371/journal.pone.0007441.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0014-24CF-0 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0019-BC38-B
Genre: Journal Article

Files

show Files
hide Files
:
Szymanski-2009-Stability of Metabol.pdf (Any fulltext), 703KB
Name:
Szymanski-2009-Stability of Metabol.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Szymanski, J.1, Author              
Jozefczuk, S.1, Author              
Nikoloski, Z.2, Author              
Selbig, J.3, Author              
Nikiforova, V.4, Author              
Catchpole, G.1, Author              
Willmitzer, L.1, Author              
Affiliations:
1Small Molecules, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753340              
2Mathematical Modelling and Systems Biology - Nikoloski, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753310              
3BioinformaticsCRG, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753315              
4System Integration, Department Willmitzer, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, ou_1753349              

Content

show
hide
Free keywords: Biochemical Processes Computational Biology/methods Computer Simulation Escherichia coli/*metabolism Escherichia coli Proteins/*metabolism Gas Chromatography-Mass Spectrometry/methods *Gene Expression Regulation, Bacterial Glucose/metabolism Hot Temperature Lactose/metabolism Metabolic Networks and Pathways Models, Biological Oxidative Stress Software Systems Biology
 Abstract: 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.

Details

show
hide
Language(s): eng - English
 Dates: 2009-10-152009
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: ISI: ISI:000270847800003
DOI: 10.1371/journal.pone.0007441
ISSN: 1932-6203 (Electronic)1932-6203 (Linking)
URI: ://000270847800003http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2759078/pdf/pone.0007441.pdf?tool=pmcentrez
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: PLoS One
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: San Francisco, CA : Public Library of Science
Pages: - Volume / Issue: 4 (10) Sequence Number: - Start / End Page: e7441 Identifier: ISSN: 1932-6203
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000277850