Comparison of Optimal Thermodynamic Models of the Tricarboxylic Acid Cycle from Heterotrophs, Cyanobacteria, and Green Sulfur Bacteria
We have applied a new stochastic simulation approach to predict the metabolite levels, energy flow, and material flux in the different oxidative TCA cycles found in E. coli and Synechococcus sp. PCC 7002, and in the reductive TCA cycle typical of chemolithoautotrophs and phototrophic green sulfur bacteria such as Chlorobaculum tepidum. The simulation approach is based on equations of state and employs an assumption similar to that used in transition state theory. The ability to evaluate the thermodynamics of metabolic pathways allows one to understand the relationship between coupling of energy and material gradients in the environment and the selforganization of stable biological systems, and it is shown that each cycle operates in the direction expected due to its environmental niche. The simulations predict changes in metabolite levels and flux in response to changes in cofactor concentrations that would be hard to predict without an elaborate model based on the law of mass action. In fact, we show that a thermodynamically unfavorable reaction can still have flux in the forward direction when it is part of a reaction network. The ability to predict metabolite levels, energy flow and material flux should be significant for understanding the dynamics of natural systems and for understanding principles for engineering organisms for production of specialty chemicals, such as biofuels.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 1188939
- Report Number(s):
- PNNL-SA-100020; KP1601010
- Journal Information:
- Journal of Physical Chemistry B, 118(51):14745-14760, Journal Name: Journal of Physical Chemistry B, 118(51):14745-14760
- Country of Publication:
- United States
- Language:
- English
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