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Development of Sulfidogenic Sludge from Marine Sediments and Trichloroethylene Reduction in an Upflow Anaerobic Sludge Blanket Reactor
Published on: October 15, 2015
Thermodynamic analysis of trinitrotoluene biodegradation and mineralization pathways
M D Shelley1, R L Autenrieth, J R Wild
1Department of Chemical Engineering, Texas A&M University, College Station, Texas 77843, USA.
Abstract:
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.
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