Comparison of Optimal Thermodynamic Models of the Tricarboxylic Acid Cycle from Heterotrophs, Cyanobacteria, and Green Sulfur Bacteria

Abstract

We have applied a new stochastic simulation approach to predict the metabolite levels, material flux, and thermodynamic profiles of the 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 modeling states using statistical thermodynamics 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 self-organization 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.

Role of horizontal gene transfers and microbial ecology in the evolution of fluxes through the tricarboxylic acid cycle

“…A possible explanation for this unique version of the TCA cycle is its connection to nitrogen metabolism through succinic semialdehyde amination to produce gamma aminobutyric acid (Zhang et al, 2016). Additionally, replacing succinyl-CoA with succinic semialdehyde as a TCA cycle intermediate decreases cumulative free energy and therefore increases forward flux through the cycle (Thomas et al, 2014). While the succinic semialdehyde shunt bypasses succinyl-CoA as an intermediate in the TCA cycle, SCS is still retained in Cyanobacteria likely due to succinyl-CoA being one of the key biochemical precursors, being necessary for synthesis of several amino acids.…”

Prediction of Metabolite Concentrations, Rate Constants and Post-Translational Regulation Using Maximum Entropy-Based Simulations with Application to Central Metabolism of Neurospora crassa

“…In order to maintain a non-equilibrium state, boundary concentrations for the initial reactant glucose 6-phosphate and final product CO 2 are set to non-equilibrium values of 2 mM and 0.1 mM, respectively. Likewise, the cofactors CoA, ATP, ADP, orthophosphate, NAD, NADH, NADP and NADPH are also fixed boundary species; these concentrations were taken from a mass spectrometry analysis of absolute metabolite concentrations from Bennett et al [25] The redox pair employed to shuttle electrons into the mitochondrial respiratory chain were taken to have equal chemical potentials, as done in previous modeling of the TCA cycle [17].…”

“…Previously, we developed and implemented a maximum entropy production approach to evaluate the dynamics of different versions of the tricarboxylic acid (TCA) cycle found in nature using stochastic kinetics [17] and have more recently generalized the concept to show how simulations can be carried out from knowledge of chemical potentials [18]. In the former study, the rate of the processes were assumed to all occur on the same timescale.…”

Multiscale Modeling in the Clinic: Drug Design and Development

“…In modeling functional guilds, only a few summary reactions are used to represent the metabolic capability of each organism. Clearly, there is a tremendous need for development of more rigorous 111 and complete models of microbial metabolism.…”