Thermodynamic analysis of trinitrotoluene biodegradation and mineralization pathways

Biodegradation of 2,4,6-trinitrotoluene (TNT) proceeds through several different metabolic pathways. However, the reaction steps which are considered rate-controlling have not been fully determined. Glycolysis and other biological pathways contain biochemical reactions which are acutely rate-limiting due to enzyme control. These rate-limiting steps also have large negative Gibbs free energy changes. Because xenobiotic compounds such as TNT can be used by biological systems as nitrogen, carbon, and energy sources, it is likely that their degradation pathways also contain acutely rate-limiting steps. Identification of these rate-controlling reactions will enhance and better direct genetic engineering techniques to increase specific enzyme levels.This article identifies likely rate-controlling steps (or sets of steps) in reported TNT biodegradation pathways by estimating the Gibbs free energy change for each step and for the overall pathways. The biological standard Gibbs free energy change of reaction was calculated for each pathway step using a group contribution method specifically tailored for biomolecules. The method was also applied to hypothetical "pathways" constructed to mineralize TNT using several different microorganisms. Pathways steps that have large negative Gibbs free energy changes are postulated to be potentially rate-controlling. The microorganisms which utilize degradation pathways with the largest overall (from TNT to citrate) negatiave Gibbs free energy changes were also determined. Such microorganisms can extract more energy from the starting substrate and are thus assumed to have a competitive advantage over other microorganisms. Results from this modeling-based research are consistent with much experimental work available in the literature. (c) 1996 John Wiley & Sons, Inc.     

Estimates of Gibbs free energies of formation of chlorinated aliphatic compounds

The Gibbs free energy of formation of chlorinated aliphatic compounds was estimated with Mavrovouniotis' group contribution method. The group contribution of chlorine was estimated from the scarce data available on chlorinated aliphatics in the literature, and found to vary somewhat according to the position of chlorine in the molecule. The resulting estimates of the Gibbs free energy of formation of chlorinated aliphatic compounds indicate that both reductive dechlorination and aerobic mineralization of these compounds can yield sufficient energy to sustain microbial growth.     

Group contribution method for thermodynamic analysis of complex metabolic networks

A new, to our knowledge, group contribution method based on the group contribution method of Mavrovouniotis is introduced for estimating the standard Gibbs free energy of formation (Δ_fG′°) and reaction (Δ_rG′°) in biochemical systems. Gibbs free energy contribution values were estimated for 74 distinct molecular substructures and 11 interaction factors using multiple linear regression against a training set of 645 reactions and 224 compounds. The standard error for the fitted values was 1.90 kcal/mol. Cross-validation analysis was utilized to determine the accuracy of the methodology in estimating Δ_rG′° and Δ_fG′° for reactions and compounds not included in the training set, and based on the results of the cross-validation, the standard error involved in these estimations is 2.22 kcal/mol. This group contribution method is demonstrated to be capable of estimating Δ_rG′° and Δ_fG′° for the majority of the biochemical compounds and reactions found in the iJR904 and iAF1260 genome-scale metabolic models of Escherichia coli and in the Kyoto Encyclopedia of Genes and Genomes and University of Minnesota Biocatalysis and Biodegradation Database. A web-based implementation of this new group contribution method is available free at http://sparta.chem-eng.northwestern.edu/cgi-bin/GCM/WebGCM.cgi.     

Computational framework for predictive biodegradation

As increasing amounts of anthropogenic chemicals are released into the environment, it is vital to human health and the preservation of ecosystems to evaluate the fate of these chemicals in the environment. It is useful to predict whether a particular compound is biodegradable and if alternate routes can be engineered for compounds already known to be biodegradable. In this work, we describe a computational framework (called BNICE) that can be used for the prediction of novel biodegradation pathways of xenobiotics. The framework was applied to 4‐chlorobiphenyl, phenanthrene, γ‐hexachlorocyclohexane, and 1,2,4‐trichlorobenzene, compounds representing various classes of xenobiotics with known biodegradation routes. BNICE reproduced the proposed biodegradation routes found experimentally, and in addition, it expanded the biodegradation reaction networks through the generation of novel compounds and reactions. The novel reactions involved in the biodegradation of 1,2,4‐trichlorobenzene were studied in depth, where pathway and thermodynamic analyses were performed. This work demonstrates that BNICE can be applied to generate novel pathways to degrade xenobiotic compounds that are thermodynamically feasible alternatives to known biodegradation routes and attractive targets for metabolic engineering. Biotechnol. Bioeng. 2009; 104: 1086–1097. © 2009 Wiley Periodicals, Inc.     

Yield prediction and stoichiometry of multi-step biodegradation reactions involving oxygenation

Microorganisms can initiate the degradation of organic compounds by oxygenation reactions that require the investment of energy and electrons. This diversion of energy and electrons away from synthesis reactions leads to decreased overall cell yields. A thermodynamic method was developed that improves the accuracy of cell yield prediction for compounds degraded through pathways involving oxygenation reactions. This method predicts yields and stoichiometry for each step in the biodegradation pathway, thus enabling modeling a multi-step biodegradation process in which oxygenations occur and intermediates may persist. EDTA and benzene biodegradation are presented as examples. The method compares favorably with other yield prediction methods while providing additional information of yields for intermediates produced in the degradation pathway.     

Consistent Estimation of Gibbs Energy Using Component Contributions

Standard Gibbs energies of reactions are increasingly being used in metabolic modeling for applying thermodynamic constraints on reaction rates, metabolite concentrations and kinetic parameters. The increasing scope and diversity of metabolic models has led scientists to look for genome-scale solutions that can estimate the standard Gibbs energy of all the reactions in metabolism. Group contribution methods greatly increase coverage, albeit at the price of decreased precision. We present here a way to combine the estimations of group contribution with the more accurate reactant contributions by decomposing each reaction into two parts and applying one of the methods on each of them. This method gives priority to the reactant contributions over group contributions while guaranteeing that all estimations will be consistent, i.e. will not violate the first law of thermodynamics. We show that there is a significant increase in the accuracy of our estimations compared to standard group contribution. Specifically, our cross-validation results show an 80% reduction in the median absolute residual for reactions that can be derived by reactant contributions only. We provide the full framework and source code for deriving estimates of standard reaction Gibbs energy, as well as confidence intervals, and believe this will facilitate the wide use of thermodynamic data for a better understanding of metabolism.     

Thermodynamic electron equivalents model for bacterial yield prediction: modifications and comparative evaluations

Modifications are made to an earlier thermodynamic model (TEEM1) for prediction of maximum microbial yields from aerobic and anaerobic as well as heterotrophic and autotrophic growth. The revised model (TEEM2) corrects for lower yields found with aerobic oxidations of organic compounds where an oxygenase is involved and with growth on single-carbon (C1) compounds. TEEM1 and TEEM2 are based on energy release and consumption as determined from the reduction potential or Gibbs free energy of (1/2)-reaction reduction equations together with losses of energy during energy transfer. Energy transfer efficiency is a key parameter needed to make predictions with TEEM2, and was determined through evaluations with extensive data sets on aerobic heterotrophic yield available in the literature. For compounds following normal catabolic pathways, the best-fit value for energy transfer efficiency was 0.37, which permitted accurate predictions of growth with a precision of 15%-20% as determined by standard deviation. Using the same energy transfer efficiency, a similar precision, but somewhat less accuracy was found for organic compounds where oxidation involves an oxygenase (estimates 8% too high) and for C1 compounds (estimates 17% too high). In spite of the somewhat lower accuracy, the TEEM2 modifications resulted in improved predictions over TEEM1 and the comparison models.     

dGPredictor: Automated fragmentation method for metabolic reaction free energy prediction and de novo pathway design

Group contribution (GC) methods are conventionally used in thermodynamics analysis of metabolic pathways to estimate the standard Gibbs energy change (Δ_rG′^o) of enzymatic reactions from limited experimental measurements. However, these methods are limited by their dependence on manually curated groups and inability to capture stereochemical information, leading to low reaction coverage. Herein, we introduce an automated molecular fingerprint-based thermodynamic analysis tool called dGPredictor that enables the consideration of stereochemistry within metabolite structures and thus increases reaction coverage. dGPredictor has comparable prediction accuracy compared to existing GC methods and can capture Gibbs energy changes for isomerase and transferase reactions, which exhibit no overall group changes. We also demonstrate dGPredictor’s ability to predict the Gibbs energy change for novel reactions and seamless integration within de novo metabolic pathway design tools such as novoStoic for safeguarding against the inclusion of reaction steps with infeasible directionalities. To facilitate easy access to dGPredictor, we developed a graphical user interface to predict the standard Gibbs energy change for reactions at various pH and ionic strengths. The tool allows customized user input of known metabolites as KEGG IDs and novel metabolites as InChI strings (https://github.com/maranasgroup/dGPredictor).     

DFT study of the V(IV)/V(V) oxidation mechanism in the presence of N-hydroxyacetamide

The oxidation mechanism of V(IV)/V(V) in the presence of N-hydroxyacetamide (acetohydroxamic acid, HL) in aqueous solution has been investigated using density functional theory (DFT) calculations aiming to contribute to the understanding of this process at a molecular level. The mechanism proposed involves formation of the *OH, *OOH, H2O2 radicals and complexes formed from the interaction of these species with VOL2 complex. The Gibbs free energy of each step of the mechanism has been evaluated. The solvation energy has been estimated by means of united atoms Hartree-Fock/polarizable continuum method (UAHF/PCM). The Gibbs free energy of the global reaction of the V(IV)/V(V) oxidation has been estimated and compared with the available experimental equilibrium constant. The difference between the calculated and experimental estimates for the reaction energy of the global equation is about 1.5 kcal mol(-1). The thermodynamic profile of the reaction mechanism has been provided and discussed in terms of the possible intermediates. The influence of the ligand and the reaction rate in terms of the steady-state approximation has been briefly discussed.     

Growth of sulfate-reducing bacteria and methanogenic archaea with methylated sulfur compounds: a commentary on the thermodynamic aspects

Methylated sulfur compounds such as dimethylsulfoniopropionate, dimethylsulfide, methanethiol, and other methylated sulfur compounds can act as sources of carbon and energy for the growth under anoxic conditions of a number of sulfate-reducing bacteria and methanogenic archaea. We summarise the range of degradative reactions that do or might occur in such organisms, and present thermodynamic data for these processes. These data enable estimates of the feasibility of the reactions as growth-supporting systems, and of the possible maximum growth yields of the bacteria and archaea catalysing them. We compare our new estimates with the few data that are currently available from the literature, and show that some published growth-yield assessments need reevaluation.     

Energetics of interactions of aromatic hydrocarbons with water

The thermodynamics of transfer of aromatic (benzene, toluene) and aliphatic (ethane, propane, butane) hydrocarbons from the gas phase into water in the temperature range 5–125°C have been analyzed in order to determine the net hydration effect of these compounds. In the case of the aromatic hydrocarbons the enthalpic contribution predominates over the entropic contribution to the Gibbs energy of hydration. This results in a negative value of the hydration Gibbs energy of aromatic hydrocarbons, in contrast to the positive Gibbs energy of hydration of aliphatic hydrocarbons. The different sign of the hydration Gibbs energies indicates that the mechanism causing hydrophobicity of aromatic hydrocarbons has different nature than that causing the hydrophobicity of aliphatic hydrocarbons. The comparison of hydration of aliphatic and aromatic hydrocarbons leads to the following thermodynamic parameters for these additional interactions between the benzene ring and water at 25°C: enthalpy −5.4 kJ/mol, entropy 26.8 J/K mol and Gibbs energy −13.4 kJ/mol. The large enthalpic contribution to the Gibbs energy of hydration of aromatic hydrocarbons probably comes from the ability of the aromatic ring to accept hydrogens from water, forming hydrogen bonds.     

Computational study of decomposition mechanisms and thermodynamic properties of molecular-type cracking patterns for the highly energetic molecule GZT

This study uses the Gaussian 03 program and density functional theory B3LYP with three basis set methods—[B3LYP/6-311+G(d,p), B3LYP/6-31+G(2d,p), and B3LYP/6-31G(d,p)]—to model the highly energetic ionic compound diguanidinium 5,5′-azotetrazolate (GZT) to research its decomposition mechanisms and thermodynamic properties. Molecular-type cracking patterns are proposed, which were initiated by heterocyclic ring opening, sequential cracking of the two five-membered rings of GZT, and simultaneous release of N₂ molecules; whereas proton transfer, bond-breaking, and atomic rearrangements were performed subsequently. Finally, 15 reaction paths and five transition states were obtained. All possible decomposition species and transition states, including intermediates and products, were identified, and their corresponding enthalpy and Gibbs free energy values were obtained. The results revealed that (1) the maximum activation energy required is 187.8 kJ mol^–1, and the enthalpy change (ΔH) and Gibbs free-energy change (ΔG) of the net reaction are ?525.1 kJ mol^–1 and ?935.6 kJ mol^–1, respectively; (2) GZT can release large amounts of energy, the main contribution being from the disintegration of the 5,5'-azotetrazolate anion (ZT^2?) skeleton (ΔH?=??598.3 kJ mol^–1); and (3) the final products contained major amounts of N₂ gas, but remaining gas molecules such as HCN and NH₃ were obtained, which are in agreement with experimental results. The detailed decomposition simulation results demonstrated the feasibility of this method to calculate the energies of the thermodynamic reactions for the highly energetic GZT and predict the most feasible pathways and the final products.     

Identification of distributed metabolic objectives in the hypermetabolic liver by flux and energy balance analysis

A methodology for inferring distributed metabolic objectives from time series flux data is developed by combining metabolic flux analysis, pathway identification, free energy balances, and nested optimization. This methodology is used to investigate the metabolic response of the rat liver to burn injury-induced whole body inflammation. Gibbs free energy changes were computed for stoichiometrically balanced sequences of reactions, or pathways, rather than individual reactions, to account for energetic coupling between reactions. Systematic enumeration of pathways proceeded by elementary flux mode (EFM) analysis. Together with stoichiometric balances and external metabolite flux measurements, the DeltaG(PATH)(o) criterion provided sufficient constraints to solve a series of nested optimization problems on the metabolic goal functions and associated flux distributions of fasted livers during the first-week time course of burn injury. The optimization results suggest that there is a consistent metabolic goal function for the liver that is insensitive to the changing metabolic burdens experienced by the liver during the first-week time course. As defined by the goal function coefficients, the global metabolic objective was to distribute the metabolic resources between amino acid metabolism and ketone body synthesis. These findings point to a role for the time-invariant structure of the metabolic reaction network, expressed as stoichiometric and thermodynamic constraints, in shaping the cellular metabolic objective.     

Comparative thermodynamic analysis of DNA--protein interactions using surface plasmon resonance and fluorescence correlation spectroscopy

We report a kinetic and thermodynamic analysis of interactions between ssDNA and replication protein A (RPA) using surface plasmon resonance (SPR) and fluorescence correlation spectroscopy (FCS) at variable temperature. The two methods yield different values for the Gibbs free energy but nearly the same value for the reaction enthalpy of ssDNA-RPA complex formation. The Gibbs free energy was determined by SPR and FCS to be -62.6 and -54.7 kJ/mol, respectively. The values for the reaction enthalpy are -64.4 and -66.5 kJ/mol. It is concluded that the difference in Gibbs free energy measured by the two methods is due to different reaction entropies. The entropic contribution to the free energy at 25 degrees C is -1.8 kJ/mol for SPR and -11.8 kJ/mol for FCS. In SPR, the reaction is restricted to two dimensions because of immobilization of the DNA molecules to the sensor surface. In contrast, FCS is able to follow complex formation without spatial restrictions. In consequence, the reaction entropy determined from SPR experiments is lower than for FCS experiments.     

Predicting biodegradation

Biodegradation is important for natural and industrial cycling of environmental chemicals. Industries and government regulators increasingly seek to know the fate of chemicals in the environment and thus prevent potential negative impacts on human or ecosystem health. However, millions of organic compounds are known, and most will remain unstudied with respect to biodegradation. This necessitates the development of organized biodegradation information coupled with predictive methods. Biodegradation prediction methods are being developed using the information contained in the University of Minnesota Biocatalysis/Biodegradation database. Heuristic rules are derived from compiled biodegradation information. Additional rules are generated by deconstructing compounds into a set of the 40 most common organic functional groups. The rules consist of deriving biochemically plausible catabolic reactions for each of the functional groups. More complex compounds, containing multiple functional groups, are analysed using higher order rules requiring prioritizing enzymatic attack and reactions cleaving functional groups. While biodegradation prediction, like weather prediction, will never be perfect, it can be an important tool for guiding industry, regulators and experimentalists.     

Thermodynamics-based metabolic flux analysis

A new form of metabolic flux analysis (MFA) called thermodynamics-based metabolic flux analysis (TMFA) is introduced with the capability of generating thermodynamically feasible flux and metabolite activity profiles on a genome scale. TMFA involves the use of a set of linear thermodynamic constraints in addition to the mass balance constraints typically used in MFA. TMFA produces flux distributions that do not contain any thermodynamically infeasible reactions or pathways, and it provides information about the free energy change of reactions and the range of metabolite activities in addition to reaction fluxes. TMFA is applied to study the thermodynamically feasible ranges for the fluxes and the Gibbs free energy change, Delta(r)G', of the reactions and the activities of the metabolites in the genome-scale metabolic model of Escherichia coli developed by Palsson and co-workers. In the TMFA of the genome scale model, the metabolite activities and reaction Delta(r)G' are able to achieve a wide range of values at optimal growth. The reaction dihydroorotase is identified as a possible thermodynamic bottleneck in E. coli metabolism with a Delta(r)G' constrained close to zero while numerous reactions are identified throughout metabolism for which Delta(r)G' is always highly negative regardless of metabolite concentrations. As it has been proposed previously, these reactions with exclusively negative Delta(r)G' might be candidates for cell regulation, and we find that a significant number of these reactions appear to be the first steps in the linear portion of numerous biosynthesis pathways. The thermodynamically feasible ranges for the concentration ratios ATP/ADP, NAD(P)/NAD(P)H, and H(extracellular)(+)/H(intracellular)(+) are also determined and found to encompass the values observed experimentally in every case. Further, we find that the NAD/NADH and NADP/NADPH ratios maintained in the cell are close to the minimum feasible ratio and maximum feasible ratio, respectively.     

Thermodynamic Analysis of Energy Transfer in Acidogenic Cultures

A global thermodynamic analysis, normally used for pure cultures, has been performed for steady‐state data sets from acidogenic mixed cultures. This analysis is a combination of two different thermodynamic approaches, based on tabulated standard Gibbs energy of formation, global stoichiometry and medium compositions. It takes into account the energy transfer efficiency, ?, together with the Gibbs free energy dissipation, ΔG_o, analysis of the different data. The objective is to describe these systems thermodynamically without any heat measurement. The results show that ? is influenced by environmental conditions, where increasing hydraulic retention time increases its value all cases. The pH effect on ? is related to metabolic shifts and osmoregulation. Within the environmental conditions analyzed, ? ranges from 0.23 for a hydraulic retention time of 20 h and pH 4, to 0.42 for a hydraulic retention time of 8 h and a pH ranging from 7–8.5. The estimated values of ΔG_o are comparable to standard Gibbs energy of dissipation reported in the literature. For the data sets analyzed, ΔG_o ranges from –1210 kJ/mol_x, corresponding to a stirring velocity of 300 rpm, pH 6 and a hydraulic retention time of 6 h, to –20744 kJ/mol_x for pH 4 and a hydraulic retention time of 20 h. For average conclusions, the combined approach based on standard Gibbs energy of formation and global stoichiometry, used in this thermodynamic analysis, allows for the estimation of Gibbs energy dissipation values from the extracellular medium compositions in acidogenic mixed cultures. Such estimated values are comparable to the standard Gibbs energy dissipation values reported in the literature. It is demonstrated that ? is affected by the environmental conditions, i.e., stirring velocity, hydraulic retention time and pH. However, a relationship that relates this parameter to environmental conditions was not found and will be the focus of further research.     

Effects of hydrated water on protein unfolding

The conformational stability of a protein in aqueous solution is described in terms of the thermodynamic properties such as unfolding Gibbs free energy, which is the difference in the free energy (Gibbs function) between the native and random conformations in solution. The properties are composed of two contributions, one from enthalpy due to intramolecular interactions among constituent atoms and chain entropy of the backbone and side chains, and the other from the hydrated water around a protein molecule. The hydration free energy and enthalpy at a given temperature for a protein of known three-dimensional structure can be calculated from the accessible surface areas of constituent atoms according to a method developed recently. Since the hydration free energy and enthalpy for random conformations are computed from those for an extended conformation, the thermodynamic properties of unfolding are evaluated quantitatively. The evaluated hydration properties for proteins of known transition temperature (Tm) and unfolding enthalpy (delta Hm) show an approximately linear dependence on the number of constituent heavy atoms. Since the unfolding free energy is zero at Tm, the enthalpy originating from interatomic interactions of a polypeptide chain and the chain entropy are evaluated from an experimental value of delta Hm and computed properties due to the hydrated water around the molecule at Tm. The chain enthalpy and entropy thus estimated are largely compensated by the hydration enthalpy and entropy, respectively, making the unfolding free energy and enthalpy relatively small. The computed temperature dependences of the unfolding free energy and enthalpy for RNase A, T4 lysozyme, and myoglobin showed a good agreement with the experimental ones.(ABSTRACT TRUNCATED AT 250 WORDS)