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Title: Optimal flux patterns in cellular metabolic networks

Abstract

The availability of whole-cell level metabolic networks of high quality has made it possible to develop a predictive understanding of bacterial metabolism. Using the optimization framework of flux balance analysis, I investigate metabolic response and activity patterns to variations in the availability of nutrient and chemical factors such as oxygen and ammonia by simulating 30,000 random cellular environments. The distribution of reaction fluxes is heavy-tailed for the bacteria H. pylori and E. coli, and the eukaryote S. cerevisiae. While the majority of flux balance investigations have relied on implementations of the simplex method, it is necessary to use interior-point optimization algorithms to adequately characterize the full range of activity patterns on metabolic networks. The interior-point activity pattern is bimodal for E. coli and S. cerevisiae, suggesting that most metabolic reaction are either in frequent use or are rarely active. The trimodal activity pattern of H. pylori indicates that a group of its metabolic reactions (20%) are active in approximately half of the simulated environments. Constructing the high-flux backbone of the network for every environment, there is a clear trend that the more frequently a reaction is active, the more likely it is a part of the backbone. Finally, I brieflymore » discuss the predicted activity patterns of the central-carbon metabolic pathways for the sample of random environments.« less

Authors:
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
936992
Report Number(s):
UCRL-JRNL-227543
TRN: US200821%%191
DOE Contract Number:
W-7405-ENG-48
Resource Type:
Journal Article
Resource Relation:
Journal Name: Chaos, vol. 17, N/A, June 28, 2007, pp. 026107; Journal Volume: 17
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; ALGORITHMS; AMMONIA; AVAILABILITY; BACTERIA; BIOLOGICAL PATHWAYS; DISTRIBUTION; METABOLISM; NUTRIENTS; OPTIMIZATION; OXYGEN

Citation Formats

Almaas, E. Optimal flux patterns in cellular metabolic networks. United States: N. p., 2007. Web. doi:10.1063/1.2737828.
Almaas, E. Optimal flux patterns in cellular metabolic networks. United States. doi:10.1063/1.2737828.
Almaas, E. Sat . "Optimal flux patterns in cellular metabolic networks". United States. doi:10.1063/1.2737828. https://www.osti.gov/servlets/purl/936992.
@article{osti_936992,
title = {Optimal flux patterns in cellular metabolic networks},
author = {Almaas, E},
abstractNote = {The availability of whole-cell level metabolic networks of high quality has made it possible to develop a predictive understanding of bacterial metabolism. Using the optimization framework of flux balance analysis, I investigate metabolic response and activity patterns to variations in the availability of nutrient and chemical factors such as oxygen and ammonia by simulating 30,000 random cellular environments. The distribution of reaction fluxes is heavy-tailed for the bacteria H. pylori and E. coli, and the eukaryote S. cerevisiae. While the majority of flux balance investigations have relied on implementations of the simplex method, it is necessary to use interior-point optimization algorithms to adequately characterize the full range of activity patterns on metabolic networks. The interior-point activity pattern is bimodal for E. coli and S. cerevisiae, suggesting that most metabolic reaction are either in frequent use or are rarely active. The trimodal activity pattern of H. pylori indicates that a group of its metabolic reactions (20%) are active in approximately half of the simulated environments. Constructing the high-flux backbone of the network for every environment, there is a clear trend that the more frequently a reaction is active, the more likely it is a part of the backbone. Finally, I briefly discuss the predicted activity patterns of the central-carbon metabolic pathways for the sample of random environments.},
doi = {10.1063/1.2737828},
journal = {Chaos, vol. 17, N/A, June 28, 2007, pp. 026107},
number = ,
volume = 17,
place = {United States},
year = {Sat Jan 20 00:00:00 EST 2007},
month = {Sat Jan 20 00:00:00 EST 2007}
}
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