Stability of Ensemble Models Predicts Productivity of Enzymatic Systems
Abstract
Stability in a metabolic system may not be obtained if incorrect amounts of enzymes are used. Without stability, some metabolites may accumulate or deplete leading to the irreversible loss of the desired operating point. Even if initial enzyme amounts achieve a stable steady state, changes in enzyme amount due to stochastic variations or environmental changes may move the system to the unstable region and lose the steady-state or quasi-steady-state flux. This situation is distinct from the phenomenon characterized by typical sensitivity analysis, which focuses on the smooth change before loss of stability. Here we show that metabolic networks differ significantly in their intrinsic ability to attain stability due to the network structure and kinetic forms, and that after achieving stability, some enzymes are prone to cause instability upon changes in enzyme amounts. We use Ensemble Modelling for Robustness Analysis (EMRA) to analyze stability in four cell-free enzymatic systems when enzyme amounts are changed. Loss of stability in continuous systems can lead to lower production even when the system is tested experimentally in batch experiments. The predictions of instability by EMRA are supported by the lower productivity in batch experimental tests. Finally, the EMRA method incorporates properties of network structure, includingmore »
- Authors:
-
- Univ. of California, Los Angeles, Los Angeles, CA. (United States).Dept. of Bioengineering; Dept. of Chemical and Biomolecular Engineering
- Univ. of California, Los Angeles, Los Angeles, CA. (United States).Dept. of Chemical and Biomolecular Engineering
- Univ. of California, Los Angeles, Los Angeles, CA. (United States). UCLA-DOE Inst.; Dept. of Bioengineering; Dept. of Chemical and Biomolecular Engineering
- Publication Date:
- Research Org.:
- Energy Frontier Research Centers (EFRC) (United States). Center on Nanostructuring for Efficient Energy Conversion (CNEEC); Univ. of California, Los Angeles, CA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER); National Science Foundation (NSF); UCLA-DOE Institute for Genomics and Proteomics
- OSTI Identifier:
- 1264421
- Grant/Contract Number:
- SC0012384; SC0001060; SC0008744
- Resource Type:
- Accepted Manuscript
- Journal Name:
- PLoS Computational Biology (Online)
- Additional Journal Information:
- Journal Name: PLoS Computational Biology (Online); Journal Volume: 12; Journal Issue: 3; Journal ID: ISSN 1553-7358
- Publisher:
- Public Library of Science
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; phosphofructokinase; thermodynamics; inhibition; hexokinase; glycolysis; metabolism; networks; pathways
Citation Formats
Theisen, Matthew K., Lafontaine Rivera, Jimmy G., and Liao, James C. Stability of Ensemble Models Predicts Productivity of Enzymatic Systems. United States: N. p., 2016.
Web. doi:10.1371/journal.pcbi.1004800.
Theisen, Matthew K., Lafontaine Rivera, Jimmy G., & Liao, James C. Stability of Ensemble Models Predicts Productivity of Enzymatic Systems. United States. https://doi.org/10.1371/journal.pcbi.1004800
Theisen, Matthew K., Lafontaine Rivera, Jimmy G., and Liao, James C. Thu .
"Stability of Ensemble Models Predicts Productivity of Enzymatic Systems". United States. https://doi.org/10.1371/journal.pcbi.1004800. https://www.osti.gov/servlets/purl/1264421.
@article{osti_1264421,
title = {Stability of Ensemble Models Predicts Productivity of Enzymatic Systems},
author = {Theisen, Matthew K. and Lafontaine Rivera, Jimmy G. and Liao, James C.},
abstractNote = {Stability in a metabolic system may not be obtained if incorrect amounts of enzymes are used. Without stability, some metabolites may accumulate or deplete leading to the irreversible loss of the desired operating point. Even if initial enzyme amounts achieve a stable steady state, changes in enzyme amount due to stochastic variations or environmental changes may move the system to the unstable region and lose the steady-state or quasi-steady-state flux. This situation is distinct from the phenomenon characterized by typical sensitivity analysis, which focuses on the smooth change before loss of stability. Here we show that metabolic networks differ significantly in their intrinsic ability to attain stability due to the network structure and kinetic forms, and that after achieving stability, some enzymes are prone to cause instability upon changes in enzyme amounts. We use Ensemble Modelling for Robustness Analysis (EMRA) to analyze stability in four cell-free enzymatic systems when enzyme amounts are changed. Loss of stability in continuous systems can lead to lower production even when the system is tested experimentally in batch experiments. The predictions of instability by EMRA are supported by the lower productivity in batch experimental tests. Finally, the EMRA method incorporates properties of network structure, including stoichiometry and kinetic form, but does not require specific parameter values of the enzymes.},
doi = {10.1371/journal.pcbi.1004800},
journal = {PLoS Computational Biology (Online)},
number = 3,
volume = 12,
place = {United States},
year = {Thu Mar 10 00:00:00 EST 2016},
month = {Thu Mar 10 00:00:00 EST 2016}
}
Web of Science
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Works referencing / citing this record:
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