In silico feasibility of novel biodegradation pathways for 1,2,4-trichlorobenzene

Finley et al. BMC Systems Biology 2010, 4:7 http://www.biomedcentral.com/1752-0509/4/7 RESEARCH ARTICLE Open Access In silico feasibility of novel biodegradation pathways for 1,2,4-trichlorobenzene Stacey D Finley1, Linda J Broadbelt1, Vassily Hatzimanikatis2* Abstract Background: Bioremediation offers a promising pollution treatment method in the reduction and elimination of man-made compounds in the environment. Computational tools to predict novel biodegradation pathways for pollutants allow one to explore the capabilities of microorganisms in cleaning up the environment. However, given the wealth of novel pathways obtained using these prediction methods, it is necessary to evaluate their relative feasibility, particularly within the context of the cellular environment. Results: We have utilized a computational framework called BNICE to generate novel biodegradation routes for 1,2,4-trichlorobenzene (1,2,4-TCB) and incorporated the pathways into a metabolic model for Pseudomonas putida. We studied the cellular feasibility of the pathways by applying metabolic flux analysis (MFA) and thermodynamic constraints. We found that the novel pathways generated by BNICE enabled the cell to produce more biomass than the known pathway. Evaluation of the flux distribution profiles revealed that several properties influenced biomass production: 1) reducing power required, 2) reactions required to generate biomass precursors, 3) oxygen utilization, and 4) thermodynamic topology of the pathway. Based on pathway analysis, MFA, and thermodynamic properties, we identified several promising pathways that can be engineered into a host organism to accomplish bioremediation. Conclusions: This work was aimed at understanding how novel biodegradation pathways influence the existing metabolism of a host organism. We have identified attractive targets for metabolic engineers interested in constructing a microorganism that can be used for bioremediation. Through this work, computational tools are shown to be useful in the design and evaluation of novel xenobiotic biodegradation pathways, identifying cellularly feasible degradation routes. Background The prevalence and widespread use of man-made chemicals ("xenobiotics”) has led to a focused effort to establish new technologies to reduce or eliminate these contaminants from the environment. Commonly used pollution treatment methods such as incineration, landfilling, and air stripping also have an adverse effect on the environment [1,2]. Additionally, these methods are costly and sometimes inefficient. Therefore, it is important to develop alternative methods of biodegradation that are effective, minimally hazardous, and economical. One promising treatment method is to exploit the ability of microorganisms to use these foreign substances * Correspondence: 2 Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL) and Swiss Institute of Bioinformatics (SIB), CH H4 625, Station 6, CH-1015 Lausanne, Switzerland for maintenance and growth, a process known as bioremediation [3]. Microorganisms provide a wealth of potential in biodegradation. It has been proposed that the ability of these organisms to reduce the concentration of xenobiotics is closely linked to their long-term adaptation to environments where these compounds exist [4-6]. Genetic engineering may be used to enhance the performance of the microorganisms such that they have the desired properties needed for biodegradation. Genetically engineered microorganisms (GEMs) have new metabolic pathways, more stable catabolic activity, and expanded substrate ranges relative to existing organisms [7]. For example, genetic engineering has been employed to design specific pathways [8] or a microbial consortium [9] for the biodegradation of an organophosphorus insecticide. Whole-genome sequencing has also proved © 2010 Finley et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Finley et al. BMC Systems Biology 2010, 4:7 http://www.biomedcentral.com/1752-0509/4/7 helpful in understanding and enhancing microorganisms for bioremediation [10]. In order to fully explore the capabilities of microorganisms in cleaning up the environment, the use of computational tools to predict novel biodegradation pathways for pollutants and gain a better understanding of the fate of these compounds in the environment would be valuable [11]. Prediction methods such as the Pathway Prediction System (PPS) [12], META [13], and others [14-18] rely on databases of rules describing biotransformations that occur in cellular and environmental processes. An alternative method is the Biochemical Network Integrated Computational Explorer (BNICE), a framework developed for the discovery of novel biochemical reactions [19-21]. BNICE has been shown to be a pathway prediction method that generates feasible biodegradation routes [22]. BNICE utilizes reaction rules derived from the Enzyme Commission (EC) classification system, which provide a compact way to describe biochemical reactions and can be used to link the degradation of xenobiotic compounds to small molecule metabolism. Given the wealth of novel biodegradation pathways obtained using computational prediction methods, it is necessary to evaluate their relative feasibility. Thermodynamic feasibility is a useful metric to evaluate potential biodegradation pathways. In the absence of experimental data for the Gibbs free energies of formation and reaction, group contribution provides an estimate of the thermodynamic properties of compounds and reactions [23] and is an effective tool in the evaluation [24,25] and reconstruction [26,27] of genome-scale models. Additionally, metabolic flux analysis (MFA) provides a means of investigating the cellular feasibility of novel pathways; that is, how implementation of the pathway influences the existing metabolism of an organism and gives rise to competition for cellular resources. MFA can be augmented with thermodynamic constraints, a methodology called thermodynamics-based metabolic flux analysis (TMFA) [24], in order to generate thermodynamically feasible flux profiles and predict cellular behavior. These tools provide a systematic evaluation of the feasibility of novel pathways within the context of the cellular environment. In this work, we describe the evaluation of novel pathways to degrade 1,2,4-trichlorobenzene (1,2,4-TCB) in the context of the cellular metabolism of Pseudomonas putida, a pollutant-degrading organism. 1,2,4-TCB is one of the most widely used chlorobenzenes [28] and has many industrial uses. Chlorobenzenes have toxic effects in humans and animals [29,30], and 1,2,4-TCB in particular is included on the list of Prior (...truncated)